CELEBRATING 20 YEARS

VISION AND AUTOMATION SOLUTIONS

FOR ENGINEERS AND INTEGRATORS WORLDWIDE

www.v is ion-systems.com

DECEMBER 2016

Embedded Vision

Tight integration improves

performance

Industrial camera survey Technology, interface and use trends revealed

High-speed imagingVision inspects hot rolled steel products

CMOS camerasCoaXPress boosts data throughput

1612VSD_C1 1 11/30/16 11:50 AM

1612VSD_C2 2 11/30/16 11:50 AM

CurrentIn 2 year

26%

12%13%

0%0%

0%0%

1%0%

32%

–

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 1

featuresdepar tments

www.vision-systems.com

• Complete Archives

• Industry News

• Buyers Guide

• Webcasts

• White Papers

• Feedback Forum

• Free e-newsletter

• Video Library

A P E N N W E L L P U B L I C A T I O N

Vision and Automation Solutions for

Engineers and Integrators Worldwide

Cover Story

13 INTEGRATION INSIGHTS

Leveraging embedded vision system

performance for more than just vision

Consolidated visual inspection, motion control, I/O,

and HMI simplifies design, improves performance.

Brandon Treece

17 PRODUCT FOCUS

CMOS cameras leverage the power of CoaXPress

Employing the CoaXPress interface standard allows

vendors to increase the data throughput of their

camera systems.

Andrew Wilson

22 MARKET SURVEY

Industrial camera technologies, interfaces and

applications

In conjunction with Framos, Vision Systems Design

has conducted a survey of camera manufacturers and

systems integrators.

Ute Häussler

25 INDUSTRY SOLUTIONS PROFILE

High-speed inspection system finds defects

in steel

Vision inspects the surfaces of hot rolled steel long

products as if they were cold, even though the

inspection takes place at a temperature of over 1,000°C.

Antonio Cruz-Lopez, Alberto Lago, Roberto Gonzalez,

Aitor Alvarez and José Angel Gutiérrez Olabarria

3 My View

4 Celebrating 20 years

5 Online@vision-systems.com

Read the latest news from our website

6 Snapshots

9 Technology Trends

CAMERA DESIGN

Image sensor technology enables very low-light imaging

PACKAGING AND PRODUCTION

Vision system simplifies blister pack inspection

HIGH-SPEED IMAGING

Vision system upgrade improves printing plate alignment

32 Ad Index/Sales Offices

December 2016

VOL. 21 | NO. 11

Combining the vision and motion systems, I/O,

and HMI into a single controller helped Master

Machinery improve performance tenfold. 13.

1612VSD_1 1 11/30/16 11:47 AM

www.vieworks.com

• 3k / 4k / 6k TDI line scan camera with highest sensitivity & resolution• Max. 250kHz line rate• Bidirectional operations with up to 256 stages• Fast transfer speed with low power consumption by the newest hybrid (CCD in CMOS) TDI sensor• CCD pixel array with high image quality and noiseless charge transfer & accumulation• Ease of use and installation provided by GenIcam Interface & easy calibration functionality• User-friendly features to improve the system: trigger analysis, encoder noise reduction & rescaler• Exposure control using optional strobe controller for applications with variable speed• CoaXPress or Camera Link Interface

For more information, email us at sales@vieworks.com

Hybrid Structure & Highest Throughput

1612VSD_2 2 11/30/16 11:47 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 3E M S D E S I G N D e c e m b e r 2 0 1 6 3

myview Alan Bergstein: Group Publisher

(603) 891-9447 alanb@pennwell.com

John Lewis: Editor-in-Chief (603) 891-9130

johnml@pennwell.com

James Carroll Jr.: Senior Web Editor (603) 891-9320

jamesc@pennwell.com

Andrew Wilson: Contributing Editor +44 7462 476477

andycharleswilson@gmail.com

Kelli Mylchreest: Art Director

Mari Rodriguez: Production Director

Dan Rodd: Senior Illustrator

Debbie Bouley: Audience Development Manager

Marcella Hanson: Ad Services Manager

Joni Montemagno: Marketing Manager

www.pennwell.com

EDITORIAL OFFICES:

Vision Systems Design

61 Spit Brook Road, Suite 401Nashua, NH 03060 Tel: (603) 891-0123 Fax: (603) 891-9328

www.vision-systems.com

CORPORATE OFFICERS:

Robert F. Biolchini: Chairman

Frank T. Lauinger: Vice Chairman

Mark C. Wilmoth: President and Chief Executive Officer

Jayne A. Gilsinger: Executive Vice President, Corporate Development and Strategy

Brian Conway: Senior Vice President, Finance and Chief Financial Officer

TECHNOLOGY GROUP:

Christine A. Shaw: Senior Vice President and Group Publishing Director

FOR SUBSCRIPTION INQUIRIES

Tel: (847) 559-7330;

Fax: (847) 763-9607;

e-mail: vsd@omeda.com

web: www.vsd-subscribe.com

Vision Systems Design® (ISSN 1089-3709), Volume 21, No. 11. Vision Systems Design is published 11 times a year in January, February, March, April, May, June, July/Au-gust, September, October, November, December by Pen-nWell® Corporation, 1421 S. Sheridan, Tulsa, OK 74112. Periodicals postage paid at Tulsa, OK 74112 and at addi-tional mailing offices. SUBSCRIPTION PRICES: USA $120 1yr., $180 2 yr., $234 3 yr.; Canada $138 1 yr., $207 2 yr., $270 3 yr.; International $150 1 yr., $225 2 yr., $295 3 yr. POSTMASTER: Send address corrections to Vision Sys-tems Design, P.O. Box 3425, Northbrook, IL 60065-3425. Vision Systems Design is a registered trademark. © Pen-nWell Corporation 2016. All rights reserved. Reproduc-tion in whole or in part without permission is prohibited. Permission, however, is granted for employees of corpo-rations licensed under the Annual Authorization Service offered by the Copyright Clearance Center Inc. (CCC), 222 Rosewood Drive, Danvers, Mass. 01923, or by calling CCC’s Customer Relations Department at 978-750-8400 prior to copying. We make portions of our subscriber list available to carefully screened companies that offer prod-ucts and services that may be important for your work. If you do not want to receive those offers and/or informa-tion via direct mail, please let us know by contacting us at List Services Vision Systems Design, 61 Spit Brook Road, Suite 401, Nashua, NH 03060. Printed in the USA. GST No. 126813153. Publications Mail Agreement no. 1421727.

John Lewis, EDITOR-IN-CHIEF

WWW.VISION-SYSTEMS.COM

John Lewis, EDITOR-IN-C

WWW VISION SYSTEMS COM

Vision 2016: On A RollLast month, many of our readers helped fuel record attendance at VISION

2016, the world’s largest machine vision tradeshow. Just shy of 10,000 attend-

ees from 58 countries visited Stuttgart, Germany during the three-day event

organized by Landesmesse Stuttgart GmbH and held from November 8-10.

As the official media partner of Messe Stuttgart in sponsoring this event,

Vision Systems Design had all hands on deck. The whole team spent three exhilarating days can-

vassing the show floor to see the latest and greatest imaging products and demonstrations show-

cased by 441 exhibitors from 28 countries.

We met with many industry veterans specializing in machine vision lighting, image sensors,

industrial cameras, frame grabbers, software, and reported on a long list of product innovations

from around the world that were introduced at the show. For those interested or unable to attend

you can view an online slideshow of these innovations at: http://bit.ly/2gHvNYa.

Senior Web Editor James Carroll also posted the following intereresting recaps of his experi-

ences each day at VISION 2016, which are available for viewing online:

• Embedded vision, hyperspectral and multispectral imaging: http://bit.ly/2fmscc7

• Imaging beyond the ordinary: http://bit.ly/2g0eVaL

• North American and European machine vision outlook: http://bit.ly/2ghr4ZM

A number of organizations presented market updates at VISION 2016. In fact, you can view

the full North American vision market update presentation that AIA Director of Market Analysis

Alex Shikany gave here: http://bit.ly/2fOXZGB. On page 22 of this issue we have a summary of

the annual Framos industrial camera market survey results, which were presented live in Stutt-

gart and focused on camera technologies, interfaces and applications.

Embedded vision was another popular topic at the show. Ten of the 90 some-odd presentations

given at VISION 2016 covered embedded vision. We continue our embedded vision coverage in

this issue on page 13, where the cover story highlights how designers can leverage emdedded design

by incorporating their main machine controller, machine vision, motion system, I/O, and HMI

all into a single controller.

A number of high-speed imaging and systems based on novel 3D and hyperspectral imaging

techniques were on display at the show. Many of these products and technologies will be reported

on in upcomming issues. In the meantime, check out contributing editor Andy Wilson’s round

up of CMOS cameras employing the CoaXPress interface standard on page 17.

Market opportunities are growing, and Vision Systems Design will serve its audience of engi-

neers and system integrators to help create leading-edge applications. As the new Editor in Chief,

I look forward to building our worldwide coverage of traditional and emerging application areas

and continuing to grow the magazine, digital media and brand through 2017 and beyond.

1612VSD_3 3 11/30/16 11:48 AM

CELEBRATING 20 YEARS

Nick SiSchkaSenior Vision Solutions Engineer

(856) 547 3488 ext 6852visionsupport@edmundoptics.com

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m4

Vision and Automation Solutions for

Engineers and Integrators Worldwide

Future architectures for CMOS image sensors

Twenty sixteen was yet another outstand-

ing year to be a participant and spectator in

the CMOS image sensor (CIS) marketplace

– with significant advancements in devices

and architectures. Viability of stacked CIS in

high-volume applications has been

proven, and is expected to dominate

CIS advances for the next 3-5 years.

Stacking delivers a smaller foot-

print for the CIS and processor

combo and overall lower power

consumption due to more efficient partition-

ing of processing functions between the two

die. A smaller footprint has advantages in

many markets, and is absolutely critical in

applications such as endoscopy. In addition,

the CIS die can be fabricated in a simplified

process that’s optimized solely around the

pixel performance and yield, resulting in

significantly lower noise, defect densities,

and non-uniformities. An ultimate goal is to

create more advanced pixels by local high

density interconnects. This allows the pixel

to be split between the upper and lower die

– for example, to allow global shutter pixels

with excellent parasitic light (in)sensitivity.

Stacking still faces challenges starting with

higher non-recurring engineering (NRE)

costs for the following: a) the cost of the stack-

ing process itself, b) costs of designing two die

with the associated complications of co-sim-

ulation and co-verification of designs that

might use different fabrication processes, c)

the need for two mask sets, and d) the added

complexities during characterization, qualifi-

cation, and production.

In certain applications, stacking can also

increase the combined sensor/processor price

over non-stacked approaches. For example, in

using wafer-level stacking, the final yield of

the bonded pair is a product of the yield of

each die. Also the two stacked die typically

need to be the same physical size. This can

be a problem for very large sensors (full frame

35mm, APS-C) and very cost-sensitive appli-

cations (i.e. IoT), where it can be difficult to

find an economic balance in die area. Again,

we expect that these problems will find solu-

tions with advances in device architectures

and smart choices in process selection.

A big part of our work at Forza Silicon is

focused on the professional/prosumer camera

markets. While there has been a great deal of

activity in high-resolution video (4K and

above), the once-humble cell phone camera

has stolen the limelight from the DSLR/digi-

tal still camera. But expect a strong response

from the “still” camera market with very un-

still like high-speed 4K video and higher

dynamic range – with performance that

might also challenge the incumbents in the

digital cinema and broadcast markets. An

exciting new trend may have started with the

announcement of a medium-format camera

aimed at non-professional photography

enthusiasts. Ultimately the pricing of this

camera will determine if we will see a signifi-

cant technology push for extra-large format

sensors in the near future.

We also continue to see a lot of activity in

the unconventional imaging applications. Var-

ious markets, including automotive and aug-

mented reality, are driving the need for 3D

image sensors, which have been addressed by

Time-of-Flight sensors. However, these con-

tinue to struggle with ambient light and the

need for an injection of significant near-infra-

red light power into the scene. These prob-

lems, and their cost impact, must be overcome

before this can become a

significant market.

Barmak

Mansoorian,

President & Co-

Founder, Forza Silicon

1612VSD_4 4 11/30/16 11:48 AM

VISION.RIGHT.NOW.

Innovative products, intelligent consulting and

extensive service. Solve your imaging projects with

speed and ease by working with STEMMER IMAGING,

your secure partner for success.

Share our passion for vision.

www.stemmer-imaging.com

–

www.vision-systems.comonline @MVTec Q&A: Machine vision software, future trends

Dr. Olaf Munkelt,

Managing Director at

MVTec Software GmbH

discusses such topics

as machine vision software (Including

HALCON 13 and MERLIC 2), future

industry trends, and application areas in

which growth could be on the horizon.

http://bit.ly/2daqI5u

Identifying trends and looking toward the future of vision

This article takes a look

back at what we learned

at the North American

vision show, The Vision

Show 2016, which was held this year

from May 3-5.

http://bit.ly/2eBSVGv

ON Semiconductor officially acquires Fairchild Semiconductor

After having

initially announced

in late 2015 that it

would acquire Fairchild

Semiconductor, ON Semiconductor has

officially completed its $2.4 billion cash

acquisition of the San Jose, CA, USA-

based company.

http://bit.ly/2cCGglb

Vision and robots team up for wine production

Robots and robotic-based

vision systems are slowly

replacing the tedious,

time-consuming tasks

involved in wine production.

http://bit.ly/2dxhwYh

OSIRIS-REx spacecraft features multi-camera vision system

Launched on September

8, NASA’s OSIRIS-REx

spacecraft, which is on a

mission to study asteroid

101955 Bennu, features three high-

resolution cameras that are based

on CCD detectors.

http://bit.ly/2dl2g3K

FLIR Systems acquires Point Grey

FLIR Systems, Inc. has

announced that it has

reached a definitive asset

purchase agreement

to acquire the business of Point Grey

Research, Inc. for approximately $253

million in cash. http://bit.ly/2fa5PqT

1612VSD_5 5 11/30/16 11:48 AM

snapshots Short takes on the

leading edge

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m6

Researchers use high speed camera to study lightningA Florida Institute of Technology (Melbourne,

FL, USA; www.fit.edu) team deployed a high-

speed camera to study atmospheric events.

As part of a grant funded by the National Sci-

ence Foundation. Dr. Ningyu Liu, an Associ-

ate Professor, wrote the grant proposal to learn

more about lightning, and shorter duration

high-altitude discharges called jets and sprites.

Liu, along with Dr. Hamid Rassoul, and a

group of Ph.D. students in the Department of

Physics and Space Sciences used a Phantom

v1210 digital ultra-high-speed camera from

Vision Research (Wayne, NJ, USA; www.

phantomhighspeed.com). Featuring a 1280 x

800 CMOS image sensor with a 28 µm pixel

size and 12-bit depth, the camera achieves

speeds of 12,000 fps at full resolution, and up

to 820,000 fps at reduced resolution. The ther-

moelectrically and heat pipe-cooled camera

features a GigE interface, 10Gb Ethernet,

direct recording to CineMag, and “quiet fans”

for vibration sensitive

applications.

Lightning strikes are

recorded from inside

and on top of buildings

on the Florida univer-

sity’s campus using the

highest frame rate possi-

ble that allows the team

to account for the large

spatial extent of light-

ing, all while recording

at up to 22 GPixels/s, ac-

cording to Julia Tilles, a Ph.D student member

of the team.

“We’re limited to roughly 100,000 fps be-

cause moving to a higher

Hack highlights vulnerability in connected devicesA recent hacking incident involving as many

as one million Chinese security cameras and

digital video recorders highlights the fact that

internet-connected cam-

eras—without proper

s a feguarding—face

the potential of being

compromised.

Attackers used Chinese-made, consumer

security cameras, digital video recorders,

and other devices to generate webpage re-

quests and data that knocked various targets

offline, according to a Wall Street Journal

article. Among the various applications and

markets within the purview of Vision Sys-

tems Design coverage, the

vulnerability of security

and surveillance cameras

comes to mind.

Tim Matthews, vice pres-

ident of marketing for the In-

capsula product line at Imperva

(Redwood Shores, CA, USA; www.imperva.

com)—a company that specializes in web se-

curity and mitigating DDoS attacks—notes

that last year, his company revealed major

vulnerabilities in CCTV cameras as a result

of not taking the proper steps to protect

against threats.

“Last year, the Imperva research revealed

that CCTV cameras in popular destinations,

like shopping malls, were being turned into

botnets by cybercriminals, as a result of

camera operators taking a lax approach to

security and failing to change default pass-

words on the devices,” he said. “CCTV cam-

eras are among the most common Internet-

of-Things (IoT) devices and Imperva first

warned about CCTV botnets in March 2014

when it became aware of

continued on page 8

continued on page 7

1612VSD_6 6 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 7

snapshots

Ford to launch fully autonomous vehicle by 2021With an eye toward launching a fully auton-

omous vehicle for ride sharing by 2021, Ford

Motor Company (Dearborn, MI, USA; www.

ford.com) has made a number of key invest-

ments in tech compa-

nies and has doubled its

team in Silicon Valley.

The company’s

intent is to have a high-

volume, fully autono-

mous Society of Au-

tomotive Engineers

level 4-capable vehicle

in commercial opera-

tion in 2021 in a ride-

hailing or ride-sharing

service. To achieve its

goals, Ford has made a

number of key investments in tech companies,

expanding its advanced algorithm, 3D map-

ping, LIDAR, and sensor capabilities. These

investments include:

Velodyne (Morgan Hill, CA, USA; www.ve-

lodynelidar.com): As previously covered on our

site (http://bit.ly/2efKyRr), Ford has invested in

Velodyne, the leader in LIDAR sensors, with

an eye on quickly mass producing a more af-

fordable automotive LIDAR sensor.

SAIPS (Tel Aviv, Israel; www.saips.co.il):

Ford has acquired the Israel-based computer

vision and machine learning company to fur-

ther strengthen its artificial intelligence and

computer vision capabilities. SAIPS develops

algorithms for image and video processing,

deep learning, signal processing, and classifi-

cation, which Ford hopes will help its auton-

omous vehicles to learn and adapt to the sur-

roundings of their environment.

Nirenberg Neuroscience LLC (New York,

NY, USA; www.nirenbergneuroscience.com):

Ford announced an exclusive licensing agree-

ment with Nirenberg Neuroscience, a ma-

chine vision company founded by neurosci-

entist Dr. Sheila Nirenberg, who cracked the

neural code the eye uses to transmit visual in-

formation to the brain. Nirenberg Neurosci-

ence has a machine vision platform for per-

forming navigation, object recognition, facial

recognition and other functions.

Civil Maps (Albany, CA, USA; www.civil-

maps.com): Ford has invested in Civil Maps,

a company that has developed a scalable 3D

mapping technique, which provides Ford with

another way to develop high-resolution 3D

maps of autonomous vehicle environments.

Ford has also added two new buildings and

150,000 square feet of work and lab space ad-

jacent to its current Research and Innovation

Center in Silicon Valley, creating a dedicated,

expanded campus in Palo Alto, with plans to

double the size of the Palo Alto team by the

end of 2017.

“The next decade will be defined by auto-

mation of the automobile, and we see auton-

omous vehicles as having as significant an

impact on society as Ford’s moving assembly

line did 100 years ago,” said Mark Fields, Ford

president and CEO. “We’re dedicated to put-

ting on the road an autonomous vehicle that

can improve safety and solve social and envi-

ronmental challenges for millions of people –

not just those who can afford luxury vehicles.”

In 2016, Ford will triple its autonomous vehi-

cle test fleet to be the largest test fleet of any au-

tomaker, bringing the number to about 30 self-

driving Fusion Hybrid sedans on the roads in

California, Arizona and Michigan, with plans to

triple it again next year.

a steep 240% increase in botnet activity on

its network, much of it traced back to com-

promised CCTV cameras.”

He continued,” As we now know, these

attacks are happening more often, and mil-

lions of CCTV cameras have already been

compromised. Whether it be a router, a

Wi-Fi access point or a CCTV camera,

default factory credentials are only there to

be changed upon installation. Imperva rec-

ommends following this security protocol

of changing default passwords on devices.”

Tim Erlin, senior director of IT secu-

rity and risk strategy at cyber security com-

pany Tripwire (Portland, OR, USA; www.

tripwire.com) echoes this sentiment, and

notes that in order to use network-con-

nected cameras, regardless of the applica-

tion, companies should be taking precau-

tionary measures.

“The use of network connected cameras

in a recent large scale Distributed Denial

of Service (DDoS) attack is a clear example

of how a seemingly innocuous connected

device might be used for malicious pur-

poses,” he said. “Security researchers have

been demonstrating attacks against IP cam-

eras for a long time.”

“Preventing attacks against connected

devices,” he added, “requires effort from

both the industry and users. Vendors need

to adhere to best practices for built-in se-

curity measures, including secure remote

access, basic encryption, and patching

known vulnerabilities. These systems

can’t be deployed without consideration

for future security updates, ideally auto-

mated updates.”

Consumers should also be mindful of

potential threats. Deploy systems with se-

curity in mind. Change default credentials

for access. Put adequate access control in

place because attackers will find open and

accessible systems if they’re available.

Most major companies, organizations,

and so on; likely go to great lengths to pro-

tect themselves against such an attack. But

for those that do not, these examples serve

as a lesson that being proactive can pay off

in the long run.

continued from page 6

continued on page 8

1612VSD_7 7 11/30/16 11:48 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m8

snapshots

Security cameras embed deep neural network processingEmbedded vision company Movidius (San

Mateo, CA, USA; www.movidius.com) has

announced a partnership with the world’s

largest IP security camera provider, Hikvi-

sion (Zhejiang, China; www.hikvision.

com), to bring deep neural network tech-

nology to the company’s cameras to perform

much higher accuracy video ana-

lytics locally.

As part of the deal, Hikvision’s cameras

will be powered by the Movidius Myriad 2

vision processing unit (VPU). Myriad 2 fea-

tures a configuration of 12 programmable

vector cores, which allows users to imple-

ment custom algorithms. The VPU offers

TeraFLOPS (trillions of floating point oper-

ations per second) of performance within a

1 Watt power envelope. It features a built-in

image signal processor and hardware accel-

erators, and offloads all vision-related tasks

from a device’s CPU and GPU.

Traditionally, notes Movidius, running

deep neural networks requires devices to

depend on additional compute in the cloud,

but the Myriad 2 VPU is a low-power device

that enables the running of advanced algo-

rithms inside the cameras themselves. This

includes such tasks as car model classifica-

tion, intruder detection, suspicious baggage

alert, and seatbelt detection.

“Advances in artificial intelligence are rev-

olutionizing the way we think about personal

and public security” says Movidius CEO,

Remi El-Ouazzane “The ability to automati-

cally process video in real-time to detect anom-

alies will have a large impact on the way cities

infrastructure are being used. We’re delighted

to partner with Hikvision to deploy smarter

camera networks and contribute to creating

safer communities, better transit hubs and

more efficient business operations.”

By utilizing deep neural net-

works and stereo 3D sensing, Hikvision has

been able to achieve up to 99% accuracy in

their advanced visual analytics applications,

including those mentioned above.

“There are huge amounts of gains to be

made when it comes to neural networks and

intelligent camera systems” says Hikvision

CEO, Hu Yangzhong. “With the Myriad 2

VPU we’re able to make our analytics offer-

ings much more accurate, flagging more

events that require a response, while reducing

false alarms. Embedded, native intelligence is

a major step towards smart, safe and efficiently

run cities. We will build a long term partner-

ship with Movidius and its VPU roadmap.”

In September, Intel announced plans to

acquire Movidius, with the deal expected

to close this year. Movidius has also collabo-

rated with DJI (http://bit.ly/2f9NU7G, Shen-

zhen, China; www.dji.com), FLIR (http://bit.

ly/2eyAPE2, Wilsonville, OR, USA; www.flir.

com) Google (http://bit.ly/2f1tOgx, Moun-

tain View, CA, USA; www.google.com) and

Lenovo (http://bit.ly/2eEOHdZ, Morrisville,

NC, USA; www.lenovo.com), among others.

continued from page 6

frame rate would make our field of view just too

small. At higher frame rates and lower resolution,

a lightning channel comes into and out of the

frame so fast that we just wouldn’t get a lot of in-

formation and would have a much lower chance

of capturing something in the field of view,” she

said. “The camera’s maximum FPS can be as

high as 570,000 fps, but pushing the camera to

perform at that rate doesn’t give us a good time-

resolution to spatial-resolution trade-off. Still,

we are experimenting with shooting at slightly

higher frame rates.”

Data captured by the camera enables the

team to examine electric field measurements

and deduce the corresponding orientation of the

channel and the direction of the current.

“The v1210 is an incredibly sophisticated

camera. When we shoot between 7,000 fps to

12,000 fps, we’re able to see some of the finer

details of a lightning flash, such as branching

and leader propagation. This resolution is high

enough for us to see many elusive processes

taking place below the cloud, and it gives us a

nice, full picture. We can also use other data sets,

such as the National Charge-Moment Change

Network (CMCN), to quantify charge moved

during a lightning strike to ground,” said Tilles.

Along with the Vision Research camera, the team

uses technology such as LMA data, NEXRAD

radar data, X-ray data, electric field data, charge-

moment-change data, and NLDN data to further

evaluate the videos they capture.

continued from page 7

When it comes to the race to get fully autono-

mous vehicles on the road, the field is certainly

becoming increasingly interesting with strategic

moves such as this one, but they are certainly not

alone in their pursuit, as many other companies,

including Google (Mountain View, CA, USA;

www.google.com), Uber (San Francisco, CA,

USA; www.uber.com), Tesla (Palo Alto, CA, USA;

www.tesla.com), BMW (Munich, Germany;

www.bmw.com), Intel (Santa Clara, CA, USA;

www.intel.com), Nissan (Yokohama, Japan; www.

nissan.com), NASA (Washington, D.C.; www.

nasa.gov), are all working toward the same goal.

With so much focus being put on the technology,

it seems that before long, the roads could be filled

with driverless cars sooner than some thought.

1612VSD_8 8 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 9

technologytrendsJohn Lewis, Editor, johnml@pennwell.com

continued on page 9continued on page 9

• PACKAGING AND PRODUCTION

Vision system simplifies blister pack inspectionUsed for small tablets/capsules or other consumer goods, blister packs are a type of pre-

formed plastic packaging that have two primary components: a cavity made from either

some form of plastic or aluminum, and the lidding made from paper, plastic, aluminum or

a lamination of soft foil and other

substances. The cavity contains

the product and the lidding seals

the product in the package.

During filling, products are

first fed properly to the pre-

formed cavities, then lidding

material gets sealed onto the

support material. Even though

every item may be identified

and inspected prior to packag-

ing, the risk of product damage

or a mishap during the blister fill-

ing process remains.

Needless to say, when it comes

HIGH-SPEED IMAGING

Vision system upgrade

improves printing plate

alignment

Designed for fast, low-cost delivery of

high-end printed graphics, flexographic

presses are giant printing machines

that can print on a variety of materi-

als including paper, film and metal foil.

This type of printing process uses flex-

ible relief plates made of thin polymer

sheets that have been coated with a

photo-sensitive surface.

After being laser engraved with relief

images of the digital artwork, these flex-

ible printing plates get wrapped around

a print cylinder and installed into the

press. Each desired color on the printed

material requires its own plate. Depend-

ing on the print job, there may be up

to ten cylinders, one for each shade of

color necessary.

During operation, the plates transfer

the ink and print the artwork onto the

passing web material. For clear, high-

quality printing, the relief image on each

plate must be aligned and properly regis-

tered with other images, print plates and

print cylinders.

Because manual plate alignment is

time consuming and error prone, the

plate mounting process has become

increasingly automated in recent years,

and machine vision systems play a key

role in reducing the time required for

pre-press preparations and improving

print quality.

To guarantee

• CAMERA DESIGN

Image sensor technology enables very low light imagingWhat do detecting a fluorescent marker

viewed under a microscope, an image of the

retina captured with an ophthalmic fundus

camera, or a surveillance image operating on

a cloudless, moonless night have in common?

All require image sensor technologies that

enable very low light imaging, 30 fps image

capture, and illuminations down to 0.1 lux.

Historically, Electron Multiplication

Charge Couple Device (EMCCD) tech-

nology has been successful in enabling the

capture of scenes with very low light levels.

This technology takes the very small charge

detected in a pixel under low light and mul-

tiplies it many times before reaching the sen-

sor’s amplifier. While this technology excells

– even down to the detection of single pho-

tons – the electron multiplication cascade

can overflow and create blooming artifacts

if signal levels entering

continued on page 11continued on page 10

continued on page 10

Figure 3: SPAN Inspection System Pvt. Ltd devel-

oped a machine vision-based blister inspection system

called Blisbeat.

1612VSD_9 9 11/30/16 11:48 AM

a)

b)

c)

Standardoutput

Bright

Dark

Final outputPixel-levelswitch

EMCCDoutput

Cameracontrol

Non-destructivesensing node

HCCDoutput register

IT-EMCCD

pixel array

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m10

technologytrends

the EMCCD register are too high, limiting

use of sensors with this technology to scenes

that do not contain any bright components.

Interline Transfer EMCCD technology

addresses these limitations directly by com-

bining the low light sensitivity available from

an electron multiplication output register

with the image uniformity, resolution scal-

ing, and electronic global shutter capabilities

of Interline Transfer CCD. This combina-

tion enables the development of image sen-

sors that can capture continuously from very

low light to bright light in designs that can

range to multiple megapixels in resolution.

“Key to the performance of this technol-

ogy is an Intra-Scene Switchable Gain fea-

ture, which avoids overflow in the EMCCD

output register under bright illumination con-

ditions by selectively multiplying only those

portions of the scene that require it,” explains

Michael DeLuca, Go to Market Manager,

Industrial and Security Division, Image

Sensor Group, ON Semiconductor (Phoe-

nix, AZ, USA; www.onsemi.com).

The output design shown (Figure 1) illus-

trates how the charge from each pixel passes

through a non-destructive sensing node that

can be read by the camera control electron-

ics to provide an initial measurement of the

signal level for each pixel. This information is

used to drive a switch in the sensor that routes

charge packets to one of two outputs based on

a camera-selected threshold.

Pixels with high charge levels (correspond-

ing to bright parts of the image) are routed

to a standard CCD output for conversion to

voltage, while pixels with low charge levels

(corresponding to dark parts of the image) are

routed to the EMCCD output for additional

amplification before conversion to voltage.

These two datasets are then merged to

generate the final image. Because the charge

Figure 1: Intra-scene Switchable Gain Output.

to product safety, package integrity and

compliance, pharmaceutical companies

can ill-afford to take such risks. After all,

incorrectly packaged or damaged prod-

ucts may result in expensive manufac-

turer recalls, potentially fatal accidents

and damage to brand reputation.

That’s why blister packaging needs

to be carefully inspected after primary

package filling and prior to second-

ary packaging. It’s not enough to just

detect the presence of a product and

identify any empty blister cavities.

Rather, today’s systems must be capa-

ble of detecting various defects such as

broken product, color variations, shape

and size variations, color spots on prod-

uct, and foreign products contained in

the blisters.

The challenge is that the increasing

demand for continuous product and

package innovation, especially in the

pharmaceutical industry, drives con-

stant improvements that hinder the

success of traditional automated visual

techniques. Not only must automated

blister inspection systems be versa-

tile enough to adapt to various blister

packaging materials and equipment,

but they must also be easy for packag-

ing equipment operators and the people

tending the machinery to alter recipes

for inspection of various products rang-

ing from tablets and capsules to dra-

gées, ampoules, and applicators.

To resolve these issues, engineers,

vision system designers and imaging

experts at SPAN Inspection System

Pvt. Ltd (Ahmedabad, Gujarat, India;

www.spansystems.in) have developed

a machine vision-based blister pack

inspection system that is dubbed Blis-

beat. The system reportedly eliminates

user dependency with automated teach

technology that the company claims

simplifies the set up and configuration

process required for product change-

Figure 2: A scene with both bright and very

dark components, imaged by a standard

IT-CCD (a), a standard EMCCD (b), and an

Interline Transfer EMCCD device (c).

continued from page 9

continued from page 9

continued on page 12

1612VSD_10 10 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 11

technologytrends

form stability, running accu-

racy and productivity with-

out machine downtime,

automated flexoprint

mounting machines

generally provide an inte-

grated, vision system

that monitors, man-

ages and adjusts

the registered

alignment of the

plate mounting based on refer-

ence points such as microdots or

crosses on flexographic printing

cylinders to ensure quality and

high precision during the print-

ing process.

When a leading Italian man-

ufacturer of flexographic print-

ing and mounting machines

wanted to modernize the vision

systems used in their equipment port-

folio, they turned to imaging special-

ist FRAMOS (Taufkirchen, Germany and

Ottawa, Canada; www.framos.com) to

design a new high-speed, high-resolution

imaging system. The new imaging systems

had to meet four main requirements to

increase the system performance, accord-

ing to Lorenzo Cassano, head of the Framos

camera business unit.

“First and most important was the need

for high speed and high resolution cam-

eras to meet the megapixel and frame rate

demands of the application, along with fast

digital interfaces for timely transmission of

the large amount of process data gener-

ated,” Cassano explains. “Second was the

need to overlook a large field of interest

from multiple points of view and to have

full control to work with high-quality optical

zooming from various distances. Next, the

solution had to be flexible in terms of adjust-

ing focus and zoom factor and, finally, had

to be available at an affordable price.”

After defining requirements, applica-

tion parameters and conditions, it took the

FRAMOS team three weeks to arrive at the

final design solution (Figure

6). During the process, engi-

neers not only had to

specify the appropri-

ate vision system com-

ponents, but also built

and tested custom pro-

totypes and individual

adaptions.

The FCB-EV7500

block camera from

Sony Corp. (Tokyo,

Japan; http://pro.sony.

com/) was selected. Running

a fast 2.4 MPixel Sony Exmor

CMOS image sensor and a 30x

optical zoom auto-focus lens,

FRAMOS engineers determined

that it delivered the high image

quality needed in full HD and

offered a dynamic range suit-

able for the application.

The corresponding external iPORT SB-

GigE OEM frame grabber kit from Pleora

Technologies (Kanata, ON, Canada; www.

pleora.com), essentially transforms the Sony

camera into a GigE Vision camera, Cassano

notes. The interface is able to control the

camera over a digital channel and to trans-

mit full-resolution video at the maximum

rate supported with low, predictable latency

over a GigE link and GigE cable.

An M110 industrial PC from Tattile

(Brescia, Italy; www.tattile.com) can run

up to six cameras for multiple points of

view, each one powered through Power

over Ethernet (PoE), having a completely

dedicated power channel for all the PoE

devices and providing camera image

streaming and full lens control.

The system transmits full-resolution

images at the maximum rate supported

by the block camera, supporting cable dis-

tances of up to 100 metres and featuring a

low, predictable latency, according to Cas-

sano. “This makes it possible to have com-

plete control of the zoom and focus of each

Sony block camera with only a single cable

connection.”

from pixels with high charge levels does not

enter the EMCCD register, this output archi-

tecture allows both very low light levels and

bright light levels to be detected while avoid-

ing the image artifacts associated with over-

flow of the EMCCD output register.

The power of this technology can be seen

in Figure 2, which shows image captures of a

single scene that includes both a bright light

as well as very dark shadows, where the dark-

est portion of the image is illuminated only

by moonlight or starlight.

A traditional image sensor (Figure 2a)

images the bright part of the image well, but

doesn’t have the sensitivity to “see” in the

very darkest part of the image. A traditional

EMCCD (Figure 2b) can be configured to

image in the very darkest part of the scene,

but when the gain is turned up to enable this

low light imaging, artifacts from the bright

part of the scene destroy the image integ-

rity. Interline Transfer EMCCD technology

(Figure 2c) allows the scene to be imaged

continuously from the brightest to the darkest

part of the image, where “dark” can extend all

the way down to illumination only by moon-

light or by starlight.

Having been moved forward from the

research labs to use in production devices,

Interline Transfer EMCCD technology is

being used today in a growing family of prod-

ucts. For example, ON Semiconductor’s KAE

02150 image sensor uses Interline Trans-

fer EMCCD technology to enable low light

image capture at 1080p (1920 x 1080) resolu-

tion while operating at 30 fps, making this

device well suited to security, surveillance,

and situational awareness applications that

require high sensitivity image capture with

video frame rates.

For higher resolution needs, the 8 MPixel

(2856 x 2856) KAE 08151 image sensor is

designed in a square aspect ratio with a 22

mm diagonal, aligning with the native opti-

cal format of many scientific microscopes

and other medical equipment. “By leveraging

the advances available with Interline Transfer

EMCCD technology,” DeLuca concludes,

“these devices are the first in a new class of

image sensors that achieve high levels of per-

formance under low lighting conditions.”

Figure 6: A fully

controllable digital

imaging system built

by FRAMOS helps

an Italian manufac-

turer of flexographic

mounting machines

achieve faster, more

precise mounting.

fi

6

sp

a

p

a

to

b

S

Jf lly

continued from page 9

1612VSD_11 11 11/30/16 11:48 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m12

technologytrends

overs (Figure 3).

“Traditional systems available in the

market today have a very complex teaching

process that is extremely difficult for oper-

ators to use. The result is an increase in

time required to make recipe changes for

new products in day to day use,” explains

Pranay Soni, R&D Lead, SPAN Inspec-

tion System Pvt. Ltd. “Our software makes

it extremely easy for operators to teach

new products. It typically takes less than

a minute, even though inspection consis-

tency must be maintained.”

The system uses either a Baumer (Rade-

berg, Germany; www.baumer.com ) VLG-

23C or a Basler (Ahrensburg, Germany;

www.baslerweb.com ) aca1920-50gc color

camera for image acquisition (Figure 4).

An M111FM16 16mm focal length lens

from Tamron (Commack, NY, USA; http://

tamron-usa.com) provides extremely sharp

images and minimal optical distortion,

according to Soni, that enables Blisbeat

to consistently detect the smallest defects.

Images with a 350 x 200mm FOV, con-

taining up to 18 blisters are processed in

parallel achieving rates of up to 800 blisters

per minute. Soni notes that images are first

thresholded in HSV color space, followed

by basic blob analysis tools for calculating

area, length, width, and convexity. Other

advance algorithms for shape and symme-

try are applied thereafter followed by color

checking of product and foreign product

detection algorithms.

Most common pharmaceutical products

can be taught automatically, according to

Soni. Users simply select a few inputs such

as the product type, the number of blis-

ters, and the type of base foil etc., and then

press a single button to activate the soft-

ware, which automatically finds and prop-

erly segments all of the product colors and

cavities within area of inspection (Figure

5). “Even if a user has to manually teach a

new product,” Soni says, “it’s really simple,

because segmentation of the product color

is done by using machine learning based

on intelligent classifiers.”

Blisbeat is equipped with multi-

touch core i7 IPC which is full

IP65 from Beckhoff Automation

(Verl, Germany; www.beckhoff.

com) and real-time Beckhoff

EtherCAT based I/O module

for connectivity and communi-

cation with the machine PLC.

“After the first two Blisbeat

installations now, our customers

are very satisfied with the soft-

ware simplicity, consistent per-

formance and robust hardware,”

says Soni. “It’s also easy to inte-

grate because Blisbeat includes

a troubleshooting feature called

Live-Scopeview that enables

users to view input/output sig-

nals online to help identify

communication errors with the

machine controller or PLC.”

Machine PLC

Activateacquisition

Transferimage

Transfer hardwaretrigger to camera for

image acquisition

Transfer a signal onevery machine cycle

for processingof images

Start

1) Image processing

2) Display results on touch

screen display

3) Send signal of

accept/reject through

EtherCAT protocol to I/O

Notify input signalfrom machine to startprocessing of image

Transfer productaccept/reject

signal

1) Acquire image

1) Performs various machine interlocks

2) Maintains accept/reject result queue

3) I/O signals troubleshooting

Figure 5: A custom-built software user interface enables operators to visualize the position

and the specific nature of the blister pack defects.

Figure 4: Blisbeat utilizes automated teach technology to simplify adaptation for handling a variety of

package types and products.

continued from page 10

1612VSD_12 12 11/30/16 11:48 AM

Motioncontroller

Machinecontroller

Other machines/factory

automation

Local HMI

IntranetSmart drive

Smart drive

Smart camera

Subsystemcontroller

Robotcontroller

Industrialsensors

Conditionmonitoring

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 13

Integration Insights

Leveraging embedded vision

system performance for more

than just visionConsolidated visual inspection, motion control, I/O,

and HMI simplifies design, improves performance.

Brandon Treece

Machine vision has long been used in indus-

trial automation systems to improve produc-

tion quality and throughput by replacing

manual inspection traditionally conducted

by humans. Ranging from pick and place and

object tracking to metrology, defect detec-

tion, and more, visual data is used to increase

the performance of the entire system by pro-

viding simple pass-fail information or closing

control loops.

The use of vision doesn’t stop with indus-

trial automation; we’ve all witnessed the mass

incorporation of cameras in our daily lives,

such as in computers, mobile devices, and

especially in automobiles. Just a few years

ago, backup cameras were introduced in auto-

mobiles, and now auto-

mobiles are shipped with

numerous cameras that

provide drivers with a full

360° view of the vehicle.

But perhaps the biggest

technological advance-

ment in the area of machine

vision has been processing

power. With the perfor-

mance of processors dou-

bling every two years and

the continued focus on

parallel processing tech-

nologies such as multicore CPUs, GPUs, and

FPGAs, vision system designers can now apply

highly-sophisticated algorithms to visual data

and create more intelligent systems.

This increase in technology opens up

new opportunities beyond just more intelli-

gent or powerful algorithms. Let’s consider

the use case of adding vision to a manufac-

turing machine. These systems are tradition-

ally designed as a network

of intelligent subsystems

that form a collaborative

distributed system, which

allows for modular design

(Figure 1).

However, as system per-

formance increases, taking this hardware-

centric approach can be difficult because

these systems are often connected through

a mix of time-critical and non-time-critical

protocols. Connecting these different systems

together over various communication proto-

cols leads to bottlenecks in latency, determin-

ism, and throughput.

For example, if a designer is attempting to

Figure 1: Systems

designed as a network

of intelligent subsys-

tems that form a col-

laborative distributive

control system allow

for modular design,

but taking this hard-

ware-centric approach

can cause bottlenecks

in performance.

Brandon Treece, Senior

Product Marketing Manager,

National Instruments, Austin,

TX, USA (www.ni.com)

1612VSD_13 13 11/30/16 11:48 AM

Intranet

Centralized controller

Visionsystem

Smart drive Camera Other machines

Industrialsensors

Conditionmonitoring

Smart drive

Motionsystem

LocalHMI

Substystemcontroller

Analog input

FPGA CPUAnalog output

Digital input

Digital output

• Any sensor

• Any protocol

• Industrially rated

• Signal conditioning

• Cameras, drives, motors, actuators

• Signal processing

• Data reduction

• Co-processing

• Custom timing, triggering and synchronization

• Custom protocols

• Fast, deterministic, closed-loop control (MHz rates)

• Safety, reliablility

• Real-time analytics

• Math and analysis libraries

• Algorithms, decision making

• Data transfer mechanisms

• Network interface

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m14

Integration Insights

develop an application with

this distributed architecture

where tight integration must

be maintained between the

vision and motion system,

such as is required in visual

servoing, major performance

challenges can be encoun-

tered that were once hidden

by the lack of processing capa-

bilities. Furthermore, because

each subsystem has its own

controller, there is actually a

decrease in processing effi-

ciency because no one system

needs the total processing per-

formance that exists across the

entire system.

Finally, because of this dis-

tributed, hardware-centric

approach, designers are forced to use dispa-

rate design tools for each subsystem—vision-

specific software for the vision system, motion-

specific software for the motion system, and so

on. This is especially challenging for smaller

design teams where a small team, or even a

single engineer, is responsible for many com-

ponents of the design.

Fortunately, there is a better way to design

these systems for advanced machines and

equipment—a way that simplifies complex-

ity, improves integration, reduces risk, and

decreases time to market. What if we shift our

thinking away from a hardware-centric view,

and toward a software-centric design approach

(Figure 2)? If we use programming tools that

provide the ability to use a single design tool

to implement different tasks, designers can

reflect the modularity of the mechanical

system in their software.

This allows designers to simplify the con-

trol system structure by consolidating differ-

ent automation tasks, including visual inspec-

tion, motion control, I/O, and HMIs within a

single powerful embedded system (Figure 3).

This eliminates the challenges of subsystem

communication because now all subsystems

are running in the same software stack on a

single controller. A high-performance embed-

ded vision system is a great candidate to serve

as this centralized controller because of the

performance capabilities already being built

into these devices.

Let’s examine some benefits of this central-

ized processing architecture. Take for exam-

ple a vision-guided motion application such

as flexible feeding where a vision system pro-

vides guidance to the motion system. Here,

parts exist in random positions and orienta-

tions. At the beginning of the task, the vision

system takes an image of the part to determine

its position and orientation, and provides this

information to the motion system.

The motion system then uses the coordi-

nates to move the actuator to the part and pick

it up. It can also use this information to cor-

rect part orientation before placing it. With

this implementation, designers can eliminate

any fixtures previously used to orient and posi-

tion the parts. This reduces costs and allows

the application to more easily adapt to new

Figure 2: A software-centric design approach allows designers to simplify their control system

structure by consolidating different automation tasks, including visual inspection, motion control,

I/O, and HMIs within a single powerful embedded system.

Figure 3: A heterogeneous architecture combining a processor with an FPGA and I/O is an ideal solution for not

only designing a high-performance vision system but also integrating motion control, HMIs, and I/O.

1612VSD_14 14 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 15

Integration Insights

part designs with only software modification.

Nevertheless, a key advantage of the hard-

ware-centric architecture mentioned above is

its scalability, which is mainly due to the Eth-

ernet link between systems. But special atten-

tion must be given to the communication

across that link as well. As pointed out previ-

ously, the challenge with this approach is that

the Ethernet link is nondeterministic, and

bandwidth is limited.

For most vision-guided motion tasks where

guidance is given at the beginning of the task

only, this is acceptable, but there could be

other situations where the variation in latency

could be a challenge. Moving to a centralized

processing architecture for this design has a

number of advantages.

First, development complexity is reduced

because both the vision and the motion system

can be developed using the same software, and

the designer doesn’t need to be familiar with

multiple programming languages or environ-

ments. Second, the potential performance

bottleneck across the Ethernet networks is

removed because now data is being passed

between loops within a single application only,

rather than across a physical layer.

This leads to the entire system running

deterministically because everything shares

the same process. This is especially valuable

when bringing vision directly into the con-

trol loop, such as in visual servoing applica-

tions. Here, the vision system continuously

captures images of the actuator and the tar-

geted part during the move until the move is

complete. These captured images are used to

provide feedback on the success of the move.

With this feedback, designers can improve the

accuracy and precision of their existing auto-

mation without having to upgrade to high-per-

formance motion hardware.

This now begs the question, what does this

system look like? If designers are going to use

a system capable of the necessary computation

and control needs of machine vision systems,

as well as the seamless connectivity to other

systems such as motion control, HMIs and

I/O, they need to use a hardware architecture

that provides the performance, as well as the

intelligence and control capabilities needed by

each of these systems.

A good option for this type of system is to

use a heterogeneous processing architecture

that combines a processor and FPGA with I/O.

There have been many industry investments

in this type of architecture, including the

Xilinx (San Jose, CA, USA; www.xilinx.com)

Zynq All-Programmable SoCs (which com-

bine an ARM processor with Xilinx 7-Series

FPGA fabric), the multi-billion dollar acquisi-

tion of Altera by Intel, and other vision systems.

For vision systems specifically, using an

FPGA is especially beneficial because of its

inherent parallelism. Algorithms can be split

up to run thousands of different ways and

can remain completely independent. But

this architecture has benefits that go beyond

just vision—it also has numerous benefits for

motion control systems and I/O as well.

Processors and FPGAs can be used to per-

form advanced processing, computation, and

decision making. Designers can connect to

almost any sensor on any bus through analog

and digital I/O, industrial protocols, custom

protocols, sensors, actuators, relays, and so on.

This architecture also addresses other require-

ments such as timing and synchronization as

well as business challenges such as productiv-

ity. Everyone wants to develop faster, and this

architecture eliminates the need for having

large specialized design teams.

Unfortunately, although this architecture

offers a lot of performance and scalability, the

traditional approach of implementing it requires

specialized expertise, especially when it comes

to using the FPGA. This introduces significant

risk to designers and can make using the archi-

tecture impractical or even impossible. How-

ever, using integrated software, such as NI Lab-

VIEW, designers can increase productivity and

reduce risk by abstracting low-level complexity

and integrating all of the technology they need

into a single, unified development environment

unlike any other alternative.

Now it’s one thing to discuss theory, it’s

another to see that theory put into practice.

Master Machinery (Tucheng City, Taiwan;

Figure 4: Using a centralized, software-centric approach, Master Machinery incorporated their

main machine controller, machine vision and motion system, I/O, and HMI all into a single con-

troller yielding 10X the performance over their competition.

A good option for this type of system is to use

a heterogeneous processing architecture that

combines a processor and FPGA with I/O.

1612VSD_15 15 11/30/16 11:48 AM

MACHINE VISION | AERIAL IMAGING | AEROSPACE | INDUSTRIAL | MICROSCOPY | INSPECTION |

ASTRONOMY | QUALITY CONTROL | MILITARY | TEST & MEASUREMENT

The applications are endless...

CCD, CMOS & XCCD

Up to 47 Megapixel

TIGER | CHEETAH | PUMA

�

�

+1 (561) 989-0006 | www.imperx.com

GigE, CoaX, U3V

CameraLink

Integration Insights

www.mmcorp.com.tw) builds semiconductor

processing machines (Figure 4). This particu-

lar machine uses a combination of machine

vision, motion control, and industrial I/O to

take chips off a silicon wafer and package

them. This is a perfect example of a machine

that could use a distributed architecture like

the one in Figure 1—each subsystem would

be developed separately, and then integrated

together through a network.

Average machines like this one in the indus-

try yield approximately 2,000 parts per hour.

Master Machinery, however, took a different

approach. They designed this machine with

a centralized, software-centric architecture

and incorporated their main machine con-

troller, machine vision and motion systems,

I/O, and HMI all into a single controller, all

programmed with LabVIEW. In addition to

achieving a cost savings from not needing indi-

vidual subsystems, they were able to see the

performance benefit of this approach as their

machine yields approximately 20,000 parts per

hour—10X that of the competition.

A key component to Master Machinery’s

success was the ability to combine numerous

subsystems in a single software stack, specifi-

cally the machine vision and motion control

system. Using this unified approach allowed

Master Machinery to simplify not only the

way they design machine vision systems but

also how they designed their entire system.

Machine vision is a complex task that

requires significant processing power. As

Moore’s law continues to add performance to

processing elements, such as CPUs, GPUs,

and FPGAs, designers can use these compo-

nents to develop highly-sophisticated algo-

rithms. Designers can also use this tech-

nology to increase performance of other

components in their design as well, especially

in the areas of motion control and I/O.

As all of these subsystems increase in per-

formance, the traditional distributed archi-

tecture used to develop those machines

gets stressed. Consolidating these tasks into

a single controller with a single software

environment removes bottlenecks from the

design process, so designers can focus on

their innovations and not worry about the

implementation.

Using this unified approach allowed Master

Machinery to simplify not only the way they

design machine vision systems but also how

they designed their entire system.

1612VSD_16 16 11/30/16 11:48 AM

product focus on

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 17

CMOS cameras leverage the power of CoaXPressEmploying the CoaXPress interface standard allows vendors to increase the data

throughput of their camera systems.

Andrew Wilson, Contributing Editor

It has been seven years since the CoaXPress

(CXP) standard was introduced at VISION

2009 in Stuttgart. Since then, the standard has

become somewhat a de-facto camera-to-com-

puter interface for high-performance camera

systems since, after usurping the well-estab-

lished Camera Link standard, CXP allows ven-

dors to increase the data throughput of their

CMOS-based camera systems.

To date, numerous camera and frame grab-

bers have endorsed the interface with a range

of CMOS and CCD cameras, frame grabbers,

cables and connectors (see “CoaXPress cam-

eras and frame grabbers tackle high-speed imag-

ing,” Vision Systems Design, January 2014).

CXP Specifications

As an asymmetric point-to-point serial com-

munication standard, the CXP-6 version

features a high speed downlink of up to

6.25Gbps per cable and a 20Mbps uplink for

communications and control. Just as Camera

Link supported a Power over Camera Link

mode, so too does CXP Power (Power over

Coax) while also offering the systems devel-

oper camera-to-computer coax cable connec-

tion lengths of up to 100m.

While a single CXP-6 high-speed link deliv-

ers speeds of 6.25Gbps, the standard offers a

number of different bit rates ranging from

CXP-1 (1.25Gbps) to CXP-6 (6.25Gbps) with

maximum camera-to-computer distances

from 212m (CXP-1) to 68m

(CXP-6). These data rates and

cable distances have been tabu-

lated at http://bit.ly/2e7rMe7.

In the design of its VCC- VCXP3M

and VCC-VCXP3R VGA cameras, for exam-

ple, CIS Corp (Tokyo, Japan, www.ciscorp.

co.jp) offers a number of selectable frame

rates that include 269 fps (CXP-1), 538 fps

(CXP2) and 536.7 fps (CXP3). To increase

this data rate further, multiple links can be

used. Indeed, today, a number of manufactur-

ers have introduced both cameras and frame

grabbers that use four CXP-6 links providing

data rates of 25Gbps.

Aggregating several links can achieve

double or quadruple the data rate of 12.5Gps

or 25Gbps, respectively. Here, the number of

links used depends on the maximum output

speed of the sensor and/or the data rate. In

the design of its CXP interface for Sony block

cameras, for example, Active Silicon (Iver,

England; www.activesilicon.com) has used a

single 2.5Gbps CXP-2 link to support all the

HD modes of the camera – 1080i and 720p at

50Hz or 60Hz–of the 1/3in 2M pixel CMOS

imager used in the camera (Figure 1).

Multiple links

Where faster megapixel imagers are used,

manufacturers must opt to provide multiple

CXP-6 links. When such sensors are used,

cameras can be configured around differ-

ent CXP configurations to provide the speed

and bit depth required. For example, JAI (San

Jose, CA, USA; www.jai.com) uses the Lin-

ce5M 2560 x 2048 CMOS sensor from Anafo-

cus (Seville, Spain; www.anafocus.com) – now

part of e2V (Chelmsford, England, UK; www.

e2v.com) – in its Lince5M-based cameras.

Studying the datasheet of the Lince5M at

http://bit.ly/2dDkZax reveals that the 2560 x

2048 1 in. CMOS imager can be operated in

12-bit mode at a maximum rate of 250 fps. At

such frame rates and bit depths, four CXP-6

links are required by JAI’s SP-5000M-CXP4

(monochrome) and SP-5000C-CXP4 (color)

cameras. However, the sensor can also be oper-

ated at less than its full data rate when interface

bandwidth is limited.

For example, the Lince5M can output full

resolution at a reduced 211 fps, 8 bit mode

Figure 1: For Sony’s FCB-H11 block camera,

Active Silicon has used a single 2.5Gbps CXP-2

link to support all the HD modes of the FCB-

H11 – 1080i and 720p at 50Hz or 60Hz–of the

1/3in 2MPixel CMOS imager used in the camera

CMOS Cameras

1612VSD_17 17 11/30/16 11:48 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m18

CMOS Cameras product focus on

CMOS Cameras with CXP interfaces

Company Model Number Data rate Sensor Other Sensor

Active SiliconIver, England, UKwww.activesilicon.com

CXP interface for Sony FCB-H11/10

Single 2.5Gbps CoaXPress link

1/3in 2M pixel CMOS 16 x 9 aspect ratio

and Sony FCB-H11 block cameras

120x zoom (H11)

AdimecEindhoven, The Netherlandswww.adimec.com

Quartz Q-2A340 340 fps 2048 x 1088 CMOS 2/3in sensor, 5.5 x 5.5μm pixel sizeCMOSIS CMV2000

Quartz Q-4A180 180 fps 2048 x 2048 CMOS 1in sensor, 5.5 x 5.5μm pixel sizeCMOSIS CMV4000

Quartz -12A180 187 fps 12Mpixel CMOS Optical size: APS-C, 5.5 x 5.5μm pixel sizeCMOSIS CMV12000

Sapphire S-25A70 73 fps 5120 x 5120 CMOS 35mm sensor, 4.5 x 4.5μm pixel sizeON Semi VITA25k

Sapphire S-25A80 80 fps 5120 x 5120 CMOS 35mm sensor, 4.5 x 4.5μm pixel sizeON Semi PYTHON25k

Norite N-5A100 100 fps 2592 x 2048 CMOS 1in, 4.8 µm x 4.8 µm pixel sizeON Semi PYTHON5000

BAP Image SystemsErlangen, Germanywww.bapimgsys.com

LC8K100CXP 80 kHz scan line

8194 px x 2 lines (Bayer)/ 8194 pixels mono, 7 x 7 μm square pixels

Awaiba Dragster

CIS CorpTokyo, Japanwww.ciscorp.co.jp

VCC-25CXP1M/R 81 fps 5120 × 5120 CMOS 35mm sensor, 4.5 x 4.5μm pixel size

VCC-5CXP3M/R 85.1fps 2592 × 2048 CMOS 1in sensor, 4.8 x 4.8μm pixel size

VCC-SXCXP3M/R 168.5 fps 1280 x 1024 CMOS 1/2in sensor, 4.8 x 4.8μm pixel size

VCC-VCXP3M/R 536.7 fps 640 x 480 CMOS 1/4in sensor, 4.8 x 4.8μm pixel size

VCC-SVCXP3M/R 386.3 fps 800 x 600 CMOS 1/3.6in sensor, 4.8 x 4.8μm pixel size

VCC-5CXP1C 80 fps 2560 x 2048 CMOS 1in image sensor, 5 x 5μm pixel size

VCC-2CXP3M 180.5 fps 1920 × 1200 CMOS 2/3in sensor, 4.8 x 4.8μm pixel size

VCC-10CXP1M/R 175 fps 3840 × 2896 CMOS 4/3in sensor, 4.5 x 4.5μm pixel size

VCC-12CXP1M/R 162 fps 4096 × 3072 CMOS 4/3in sensor, 4.5 x 4.5μm pixel size

VCC-16CXP1M 124 fps 4096 x 4096 CMOS 35mm sensor, 4.5 x 4.5μm pixel size

e2VChelmsford, England, UKwww.e2v.com

ELiiXA+ 12k 200KHz 200 kHz 11008 at 200KHz linescan sensor, 5 x 5 μm pixel size

ELiiXA+ 16k 140KHz 140 kHz 16384 or 8192 linescan sensor, 5 x 5 μm pixel size

ELiiXA+ 16k/8k 100KHz 100 kHz 16384 or 8192 linescan sensor, 5 x 5 μm pixel size

ELiiXA+ 16K/8k Colour 2335 pix/s 16384 or 8192 linescan sensor, 5 x 5 μm pixel size

ImperxBoca Raton, FL, USAwww.imperx.com

C2880 135 fps 2832 x 2128 1in sensor, 4.7 x 4.7 μm pixel sizeON Semi KAC-06040

C4080 70 fps 3000 x 4000 4/3in sensor, 4.7 x 4.7 μm pixel sizeON Semi KAC-12040

IO IndustriesLondon, ON, Canadawww.ioindustries.com

Flare 50MP 30.9 fps 7920 x 6004 35mm, 4.6 x 4.6μm pixel size

Flare 12MP 187 fps (8-bit) 4096 x 3072APS-C (28.1mm diagonal), 5 x 5μm pixel size

Flare 4MP 140 fps (8-bit) 2048 x 2048 1in sensor, 5 x 5μm pixel size

Flare 2MP 264 fps (8-bit) 2048 x 1088 2/3in sensor, 5 x 5μm pixel size

ISVISeoul, South Koreawww.isvi-corp.com

IC-M12S-CXP/IC-C12S-CXP

181 fps (8-bit) 4096 x 3072APS-C (28.1mm diagonal), 5.5 x 5.5μm pixel size

CMOSIS CMV12000

IC-M25CXP/IC-C25CXP 53 fps 5120 x 5120 35mm sensor, 4.5 x 4.5μm pixel size

JAISan Jose, CA, USAwww.jai.com

SW-2000M-CXP 80 kHz 2048 x 1 40.96mm sensor, 20 x 20μm pixel size Custom CMOS

SP-5000M-CXP2 and SP-5000C-CXP2

211 fps 2560 x 2048 1in sensor, 5 x 5μm pixel sizee2V (Anafocus) Lince5M

SP-20000M-CXP2 and SP-20000C-CXP2

30 fps 5120 x 3840 35mm, 6.4 x 6.4μm pixel sizeCMOSIS CMV20000

SW-2000Q-CXP2 80 kHz 2048 x 4 Color line scan, 20 x 20μm pixel size

SW-2000T-CXP2 80 kHz 2048 x 3 Color line scan, 20 x 20μm pixel size

SP-12000M-CXP4 and SP-12000C-CXP4

189f ps 4096 x 3072APS-C (28.1mm diagonal), 5.5 x 5.5μm pixel size

CMOSIS MV12000

SP-5000M-CXP4 and SP-5000C-CXP4

253 fps 2560 x 2048 1in sensor, 5 x 5μm pixel sizee2V (Anafocus) Lince5M

1612VSD_18 18 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 19

CMOS Cameras with CXP interfaces

Company Model Number Data rate Sensor Other Sensor

Lambert InstrumentsGroningen, The Netherlandswww.lambertinstruments.com

HS540M 540 fps 1696 x 1710 8 x 8μm pixel size

Laon PeopleBundang-gu, South Koreawww.laonpeople.com

LPMVC-CXP12M 190 fps 4096 x 3068 28.1mm sensor, 5 x 5μm pixel size

LPMVC-CXP25M 72 fps 5120 x 5120 35mm sensor, 4.5 x 4.5μm pixel size

MikrotronUnterschleissheim, Germanywww.mikrotron.de

EoSens 3CXPm/c 566 fps 1696 x 1710 1in sensor, 8 x 8μm pixel sizeON Semi LUPA3000

EoSens 4CXPm/c 563 fps 2336 x 1728 4/3in sensor, 7 x 7μm pixel size Alexima AM41

EoSens 25CXPm/c 80 fps 5120 x 5120 35mm sensor, 4.5 x 4.5μm pixel sizeON Semi VITA25K

EoSens 12CXP+ 165 fps 4096 x 3072 35mm sensor, 4.5 x 4.5μm pixel sizeOn SemiPython

EoSens 25CXP+ 80 fps 5120 x 5120 35mm sensor, 4.5 x 4.5μm pixel sizeOn SemiPython

NEDOsaka, Japanwww.ned-sensor.co.jp

XCM20160T2CXP 68/125 kHz 2048 x 1 28.672mm line scan, 14 x 14μm pixel size

XCM40160CXP 3.58 kHz 4096 k x 1 28.672mm line scan, 7 x 7μm pixel size

XCM60160CXP 24.88 kHz 6144 x 1 43.008mm line scan, 7 x 7μm pixel size

XCM80160CXP 18.65 kHz 8192 x 1 57.344mm line scan, 7 x 7μm pixel size

XCM80160T2CXP 33.58 kHz 8192 x 1 57.344mm line scan, 7 x 7μm pixel size

XCM16K04GT4CXP 68.97 kHz 16384 x 157.344mm line scan, 3.5 x 3.5μm pixel size

SCAN-12MX 190 fps 4096 × 3072 5.5µm × 5.5µm pixel size

SCAN-25MX 73 fps 5120 x 5120 4.5 x 4.5μm pixel size

OptronisKehl, Germanywww.optronis.com

CP70-12-M-167 / CP70-12-C-167

167 fps 4080 x 3072 5.5 x 5.5μm pixel sizeCMOSIS CMV12000

CP80-3-M-540 / CP80-3-C-540

540 fps 1696 x 1710 8 x 8μm pixel sizeON SemiLUPA3000

CP80-4-M-500 / CP80-4-C-500

500 fps 2304 x 1720 7 x 7μm pixel size Alexima AM41

CP80-25-M-72 / CP80-25-C-72

72 fps 5120 x 5120 4.5 x 4.5μm pixel sizeON Semi VITA25K

CP70-12-M-188 / CP70-12-C-188

188 fps 4080 x 3072 5.5 x 5.5μm pixel size

CP70-HD-M-900 / CP70-HD-C-900

908 fps 1920 x 1080 5.5 x 5.5μm pixel size

CP70-1-M/C-1000 1040 fps 1280 x 1024 6.6 x 6.6μm pixel sizeLuxima LUX1310 Global Shutter CMOS

SVS-VistekSeefeld, Germanywww.svs-vistek.com

hr25000MCX/CCX 80 fps 5120 x 5120 35mm, 4.5 x 4.5μm pixel sizeON Semi PYTHON25K

Toshiba TeliTokyo, Japanwww.toshiba-teli.co.jp

CSX12M25CMP19 25 fps 4096 x 3072 6 x 6μm pixel sizeProprietary 1.9 type sensor

VieworksGyeonggi-do, Republic of Koreawww.vieworks.com

VC-4MX-M/C 144 144 fps 2028 x 20448 1in, 5.5 x 5.5μm pixel sizeCMOSIS CMV4000

VC-12MX-M/C 180 180 fps 4096 x 3072 APS-like, 5.5 x 5.5μm pixel sizeCMOSIS CMV12000

VC-25MX-M/C 72 72 fps 5120 x 5120 35mm, 4.5 x 4.5μm pixel sizeON SEMI VITA25K

VT-18K3.5X-H140/H80 142 kHz/80 kHz 1784 x 256 TDI camera, 3.5 x 3.5μm pixel size Proprietary

VT-12K5X-H200/H100 200 kHz/100kHz 12480 × 256 TDI camera, 5 x 5μm pixel size Proprietary

VT-9K7X-H250/H120 250 kHz/125 kHz 8912 x 128 TDI camera, 7 x 7μm pixel size Proprietary

VT-6K10X-H170 172 kHz 6240 × 128 TDI camera, 10 x 10μm pixel size Proprietary

Table 1: Today’s line-scan and area-array cameras that support the CXP standard use a number of off-the-shelf imagers from just a handful of

companies.

1612VSD_19 19 11/30/16 11:48 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m20

CMOS Cameras product focus on

using two CXP-6 links, a fact

that has been realized in the

design of JAI’s SP-5000M-CXP2

and SP-5000C-CXP2 CXP cam-

eras (Figure 2). A number of ben-

efits result including fewer driv-

ers and equalizers to implement

the CXP interface and allowing deployment

of dual-camera configurations using four-link

CXP frame grabbers available from Active Sil-

icon, BitFlow (Woburn, MA, USA; www.bit-

flow.com), Euresys (Angleur, Belgium; www.

euresys.com) and others.

Four CXP-6 links are also used to support

the data rates from image sensors such as the

AM41 from Alexima (Pasadena, CA, USA;

www.alexima.com). While Mikrotron (Unter-

schleissheim, Germany; www.mikrotron.de)

uses the device in its EoSens 4CXPm/c Optro-

nis (Kehl, Germany; www.optronis.com) uses

the AM41 in its CP80-4-M/C-500 camera (see

“CMOS Cameras with CXP Interfaces” table

on page 18 of this issue).

Interestingly, the specifications of these

cameras found on the Mikrotron and Optro-

nis websites differs very slightly from the origi-

nal AM41V4 data sheet specification that can

be found at http://bit.ly/2ebbzVz. Regardless,

using four CXP links allows both cameras to

transfer 4Mpixel images at data rates of approx-

imately 500 fps at full resolution.

More than four

While many currently available frame grab-

bers support such four-link cameras, Kaya

Instruments (Haifa, Israel; www.kayainstru-

ments.com) Komodo CXP frame grabber is

capable of receiving image data from up to

eight CoaXPress links in single, dual, quad or

octal modes (Figure 3). Thus, it can be used

to simultaneous capture image data from two

quad CXP-6 link cameras at a maximum

data rate of 25Gbps per camera allowing dual

camera systems with a

maximum data rate

of 50Gbps on a single

frame grabber.

Interestingly, at

the time of writing,

Vieworks (Gyeonggi-

do, Republic of

Korea; www.vieworks.com)

12MPixel 8-connection CoaX-

Press camera, the VC-12MX2-

M330, announced at last month’s

VISION Stuttgart trade show,

was shown coupled to two Eure-

sys Coaxlink Quad G3 frame

grabbers running at 330 fps. Also showcased

were eight new TDI camera models featuring

proprietary, hybrid TDI (Time Delayed Inte-

gration) sensors that combine CCD-based

pixel array with a light sensitive and noiseless

charge transfer and accumulation process,

with fast CMOS readout electronics. The

resulting high sensitivity and high dynamic

range sensor is said to offer CCD-like image

quality, with the speed and low power con-

sumption commonly found in CMOS sensors.

However, such designs have not been widely

adopted for reasons that may include the cost of

adding additional drivers and equalizers in the

cameras and the additional cost of the cables

required to implement single camera/frame

grabber octal CXP-6 systems. There is not a

reason why this could not be accomplished,

however, since cameras that use devices such

as the CMV12000 from CMOSIS (Antwerp,

Belgium; www.cmosis.com) could benefit

from such implementations.

Indeed, the specification of the CMOSIS

12MPixel 4096 x 3072 device running at

300 fps in 10-bit mode would necessitate a

data rate of approximately 38Gbps and eight

CXP-6 links. This necessitates camera devel-

opers such as IO Industries (London, ON,

Canada; www.ioindustries.com) that use the

CMV12000 in its Flare 12M180-CX, a four-

channel CXP-6 implementation, to run the

device at a slower data rate of 187 fps.

Going faster

It is unlikely that many camera and (perhaps)

other frame grabber vendors will adopt octal

CXP-6 based implementations, but rather

wait for the next generation of higher-speed

drivers and equalizers. This will increase the

current maximum data rate from the existing

6.25Gbps (CXP-6) by adding 10Gbps (CXP-

10) and 12.5Gbps (CXP-12.5). Of the number

of camera manufacturers contacted for this

article, many were still awaiting to receive

samples of higher speed drivers and equalizers.

“All of our cameras are designed around

current 6.25Gbps CXP-6 standard due to the

unavailability of the new CXP driver chip,”

says Yusuke Muraoka, President of CIS Corp,

“but we will definitely look into the faster stan-

dard once the standard and the devices are

ready.” Similarly, Mikrotron did not show a

CXP-10 or CXP-12.5 camera at the VISION

Show last month.

“CXP-12 is on the company’s roadmap and

will find its way into Mikrotron CXP cam-

eras but not until mid to late next year,” says

Steve Ferrell, Head of Business Development

at Mikrotron’s North American Office (Poway,

CA, USA). “I understand that Microchip Tech-

nology (Chandler, AZ, USA; www.microchip.

com) is not scheduled to go into production

with parts until Q3 2017,” he added.

While many camera vendors appear to be

either lacking sample ICs to increase the speed

of their CXP-based cameras, it seems that

frame grabber vendors have already received

engineering samples. Marc Damhaut, Chief

Executive Officer of Euresys notes the com-

pany is currently working on prototypes and

proofs of concept for these two new versions

Figure 2: At a

reduced 211 fps, JAI’s

SP-5000M-CXP2

(greyscale) and SP-

5000C-CXP2 (color) CXP

cameras require the use

of two CXP-6 links.

Figure 3: Kaya Instruments Komodo CXP

frame grabber is capable of receiving image

data from up to eight CoaXPress links in single,

dual, quad or octal modes.

1612VSD_20 20 11/30/16 11:48 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 21

of the standard (Figure 4).

“We have built a prototype

of CXP-10 frame grabber using

engineering samples of the forth-

coming Microchip Technology

devices,” he says. The company

chose last month’s VISION 2016

show in Stuttgart to display the

frame grabber in cooperation

with Microchip and Adimec

(Eindhoven, The Netherlands;

www.adimec.com). “We’re also

working on validating a CXP-12

interface based on Macom

(Lowell, MA, USA; www.

macom.com) devices.”

Active Silicon is also developing a frame

grabber to support CXP-10 and CXP-12.5,

according to Colin Pearce, CEO. Although

this was also announced at VISION 2016, the

company did not exhibit the board.

Speed benefits

Developers of high frame rate cameras use

devices such as CMOSIS’ CMV12000 to

achieve full device frame rates of 38Gbps

using quad CXP-12.5 links and single quad-

link frame grabbers. Line-scan camera man-

ufacturers may benefit from reducing the

number of CXP cables required and increase

camera throughput with the emerging CXP-10

and CXP-12.5 standards.

At present, for example, the XCM16K-

04GT4CXP, 16384 x 1 line-scan camera

from NED (Osaka, Japan; www.ned-sensor.

co.jp) uses four CXP-5 connectors to output

data at 68.97kHz. This number of connec-

tors could be reduced should the company

choose to implement the emerging CXP stan-

dards. While the speed and resolution of both

line-scan and area-scan CMOS imagers will

continue to increase to meet the demands of

applications such as industrial inspection and

medical imaging, so too will the high-speed

interfaces needed to support them.

Formerly, relatively small companies led

such CMOS device innovations. Lately, how-

ever, there has been rapid consolidation in the

marketplace with companies such as Anafo-

cus, CMOSIS and Truesense Imaging (Roch-

ester, NY, USA) being acquired by e2V, the

AMS Group (Premstaetten, Austria; http://

ams.com) and ON Semiconductor (Phoenix,

AZ, USA; www.onsemi.com), respectively.

Whether this somewhat stifles the innova-

tion of novel CMOS imagers remains to be

seen. Camera companies wishing to more

effectively differentiate their products, how-

ever, will need to seek newer sensor start-ups

or invest in custom CMOS imagers.

Figure 4: Euresys has built a prototype of CXP-10 frame

grabber using engineering samples of Microchip Technolo-

gy devices.

Active SiliconIver, Englandwww.activesilicon.com

AdimecEindhoven, The Nether-landswww.adimec.com

AleximaPasadena, CA, USAwww.alexima.com

The AMS GroupPremstaetten, Austriahttp://ams.com

AnafocusSeville, Spainwww.anafocus.com

AwaibaFunchal, Madeira, Portugalwww.awaiba.com

BAP Image SystemsErlangen, Germanywww.bapimgsys.com

BitFlowWoburn, MA, USAwww.bitflow.com

CIS CorpTokyo, Japanwww.ciscorp.co.jp

CMOSISAntwerp, Belgiumwww.cmosis.com

e2VChelmsford, Englandwww.e2v.com

EuresysAngleur, Belgiumwww.euresys.com

ImperxBoca Raton, FL, USAwww.imperx.com

IO IndustriesLondon, Ontario, Canadawww.ioindustries.com

ISVISeoul, S. Koreawww.isvi-corp.com

JAISan Jose, CA, USAwww.jai.com

Kaya InstrumentsHaifa, Israelwww.kayainstruments.com

Lambert InstrumentsGroningen, The Nether-landswww.lambertinstruments.

com

Laon PeopleBundang-gu, South Koreawww.laonpeople.com

Luxima TechnologyPasadena, CA, USAwww.luxima.com

MACOMLowell, MA, USAwww.macom.com

Microchip TechnologyChandler, AZ, USAwww.microchip.com

MikrotronUnterschleissheim, Ger-manywww.mikrotron.de

NEDOsaka, Japanwww.ned-sensor.co.jp

ON SemiconductorPhoenix, AZ, USAwww.onsemi.com

OptronisKehl, Germanywww.optronis.com

SVS-VistekSeefeld, Germanyww.svs-vistek.com

Toshiba TeliTokyo, Japanwww.toshiba-teli.co.jp

VieworksGyeonggi-do, Republic of Koreawww.vieworks.com

Companies mentioned

For more information about CoaXPress products, visit Vision Systems Design’s Buyer’s Guide buyersguide.vision-systems.com

1612VSD_21 21 11/30/16 11:48 AM

<150 26%

23%

21%

11%

6%

13%

150–350

350–650

650–1000

1000–3000

>3000

$

How many industrial cameras in percent didyou sell in the following price ranges?

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m22

Industrial camera applications, technologies and interfacesManufacturers and integrators review industrial camera

market status and future trends.

Ute Häussler

In collaboration with Vision Systems

Design and Inspect magazines, FRAMOS

(Taufkirchen, Germany; www.framos.

com) has conducted a market survey of

trends, interfaces and future developments

in camera technology. The study, based on

the opinions of 52 users and 8 manufactur-

ers—55% who were from Europe, 23% from

North and South America, and 22% from

Asia/The Middle East—were presented at

the VISION 2016 show in Stuttgart. Europe

ranked first in terms of both purchasing and

production at 62% and 43%. Manufacturers

also produce in Asia (13%) and in America

(6%). Behind Europe, Asia and America have

equally strong purchasing markets, at 28%.

Compared with 2015, American production

has declined to 28%, which can be ascribed to

weaker survey participation from North and

South America.

While camera vendors cited that measure-

ment and logistics comprised 50% and 13% of

sales respectively, production automation and

quality assurance applications ranked equally

at 63%. Medical diagnos-

tics and scientific applica-

tions also ranked equally

at 38%. Similar results were

reflected by camera users

who said that 48% of the

cameras they purchased

are deployed in automation applications, 46%

in quality assurance, 40% in measurement,

and 29% in scientific applications. Medical

diagnostic applications account for 10% of

user camera deployments. While traffic appli-

cations, including vehicle assistance systems

are significant to manufacturers, representing

25% and 13% of sales respectively, they appear

to be less relevant to users, with deployment

into these application ranking at only 10% and

2% respectively.

As in past years, both camera manufacturers

and systems developers see a continued growth

in the image processing and machine vision

industry with 90% of users intending to intro-

duce or to replace existing systems within the

next two years.

Camera pricing

After a high of 70% in 2014, manufacturers pro-

duction roadmaps have steadily declined to

44% for production of cameras in the mid-price

range between $150 and $650, which reveals

some price stabilization after successive drops

in the previous years. Low-

cost cameras less than $150

are least significant to manu-

facturers and users in terms of

percentage, at 26% and 11%,

respectively. Compared with

2015, high-priced cameras

from $650/$1,000/$3,000 have dropped by 12%

points (Figure 1). As a result, production of cus-

tomized cameras for specific applications seems

to be a strong selling point, and a market advan-

tage, for smaller camera manufacturers.

CMOS vs. CCD

In the light of Sony’s discontinuation of CCD

imagers, users see the greatest growth for com-

panies such as ON Semiconductor, which cur-

rently holds a 29% market share. The declines

foreseen by users and manufacturers for Sony

in last year’s study haven’t materialized with

32% of all camera manufacturers currently

relying on Sony. In 2 years, Sony is expected

Figure 1: The fact that camera costing more

than $1,000 account for almost 20% of man-

ufacturer sales indicates strong demand for

high-end cameras in many applications.

Ute Häussler, Manager of

Marketing Communications,

FRAMOS (Taufkirchen, Ger-

many; www.framos.com)

MARKETS U R V E Y

1612VSD_22 22 11/30/16 11:48 AM

CurrentIn 2 years11%

2%8%

10%

13%10%

1%1%

0%0%

15%18%

33%41%

1%4%

0%4%

0%1%

17%9%

Firewire

USB 2.0

USB 3.0

Camera Link

Camera Link HS

Ethernet

GigE(Gigabit Ethernet)

Dual GigE

10GigE

CoaXpress

Others

How often do you use cameras with thefollowing interface types – now and

expected in 2 years?

to grow back to the 37% levels it had before

the discontinuation. Even more users this year

rely on Sony compared to last year, with an

increase from 35% to 53%.

Camera vendors cite that CMOS technol-

ogy accounts for 85% of camera sales. Camera

users expect to reach this purchasing level in

the next two years. With no increase com-

pared to last year, 51% of users rely on CMOS

today but are predicting faster growth to 83%,

in contrast to 70% in 2015. Based on the shift

from CCD technology, e2v benefits with ref-

erence to manufacturers (from 3% to 12%)

and customer-specific sensors (from 4% to

19%) with an equally positive forecast.

While approximately 30% of users relied

on sensors under 1 MPixel last year, in 2016,

only 10% do. This significant decline can be

marked as growth in the 1-3 MPixel (+10%

points), the 3-5 MPixel (+2% points), and the

5-10 MPixel (+3% points) categories. Man-

ufacturers as well as users expect a focus

on frame rates between 25 fps and 60 fps

today and in the coming two years. At the

same time, compared to last year, significant

increases in the area of over 100 fps (+13%

points for users) and 200 fps (+14% points for

manufacturers) have taken place.

Standard interfaces

GigE Vision dominates according to man-

ufacturers, with 33%, followed by Ether-

net with 15%. Compared with last year and

based on a low proportion of American partic-

ipants, the previously high Ethernet percent-

age has been reduced. Manufacturers and

users expecting USB 3.0 and GigE Vision to

grow fastest with an increase of 8% and 10%

points, respectively.

More than 75% of manufacturers and,

60% of users expect bandwidths greater than

5 GB to become relevant or very relevant.

50% of manufacturers believe that USB 3.1

is the most important interface for high-speed

applications, followed by 38% for 10 GigE. In

contrast, 44% of users favor 10 GigE for fast

transmission, and only 37% of users vote for

USB 3.1.

Figure 2: Among systems integrators, the

GigE standard proved the most popular fol-

lowed by Camera Link and USB 3.

1612VSD_23 23 11/30/16 11:48 AM

ProfileIn

du

str

y S

olu

tio

ns

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m24

High-speed inspection system finds defects in steelVision inspects the surfaces of hot rolled steel long products as if they were cold, even

though the inspection takes place at a temperature of over 1,000°C.

Antonio Cruz-Lopez, Alberto

Lago, Roberto Gonzalez, Aitor

Alvarez and José Angel

Gutiérrez Olabarria

To produce seamless steel tubes, a steel billet

is transported into a furnace where it is first

heated. Next, the billet is pierced to form a

thick-walled hollow shell, after which a man-

drel bar is inserted into the shell. The shell then

undergoes elongation rolling in a mandrel mill.

Following the elongation process, the billet is

conveyed to a push bench, where it is pushed

through a series of roller cages. The result is that

a hollow length of steel tubing with consecu-

tively smaller wall thicknesses is formed.

As effective as the hot rolling process is,

the roller cages in the push benches can

sporadically produce marks and defects on

the surface of the steel that are extremely diffi-

cult to detect in hot conditions. Hence, in their

quality improvement programs, many manu-

facturers look to identify such defects as early

as possible to avoid producing tons of defective

material at considerable expense.

Vision system

To resolve those issues, engineers at Tecna-

lia (Derio, Bizkaia, Spain; www.tecnalia.

com) have developed a machine vision system

dubbed Surfin’ that can enable steel manufac-

turers to detect such defects as the steel ema-

nates from the push bench (Figure 1). The de-

tection of such defects provides manufacturers

with an indication of any issues in the produc-

tion process, enabling them to perform pre-

ventative maintenance on the push benches at

an early stage and preclude any defective steel

tubes from being delivered to their customers.

The typical defects found on the surface

of such tubes generated by the roller cages

usually follow a repetitive pattern and con-

tinue to appear until the rolling stands are

changed. They can include tears or rips in the

Antonio Cruz-Lopez, Alberto La-

go, Roberto Gonzalez, Aitor Alvarez and

José Angel Gutiérrez Olabarria, Machine

Vision Engineering Team, Tecnalia, C/

Geldo 700, 48160 Derio, Bizkaia, Spain

(www.tecnalia.com).

Figure 1: Engineers at Tecnalia have devel-

oped a vision system called Surfin’ that can

enable steel manufacturers to detect defects

in steel tubing as the steel emanates from a

push bench at over 1000oC.

1612VSD_24 24 11/30/16 11:48 AM

1

a) b)

32

1

a) b) c)

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 25

Industry Solutions Profile

surface, rolling stand blocking marks, cracks

and detached steel which is later pasted onto

another part of the surface of the steel tube.

The challenges faced by the developers were

not trivial. The conditions in such a produc-

tion environment are extreme. Not only are the

steel tubes produced at a relatively high speed of

6-7m/sec (Surfin’ can work up to 10 m/sec), the

temperature of the steel as it emanates from the

roller cages is about 1000ºC. Compounding the

inspection problem is that the environment is

dirty and water and oil vapor are present.

As the hot surface of the steel radiates light

that is directly related to thermal emission in

the IR, red, orange and yellow bands, captur-

ing an image of all the light reflected by the

surface would saturate the sensor in a camera,

since the camera would be sensitive to all the

radiation emitted by the steel tube. To solve

this, the Surfin’ system (patent ES2378602 and

EP2341330) uses light of a wavelength far from

the emitted spectrum of the incandescent steel.

Images that reach the cameras in the system

are then optically filtered with a narrow opti-

cal band-pass filter from Edmund Optics (Bar-

rington, NJ, USA; www.edmundoptics.com)

centered on 470nm with a width of 10nm and

an infrared (IR) radiation filter. Both filters

enable the CCD cameras to only receive radi-

ation in the desired wavelength band, while

the incorporation of the IR filters protects the

electronic systems from heat radiation. The

controlled lighting technique allows the system

to capture images of the entire surface of the

tube as if it were cold.

To enable the system to capture a 360°image

of the surface of the steel tube, the system uses

three sets of 14.000 lines/s Teledyne DALSA

(Waterloo, ON, Canada; www.teledynedal-

sa.com) Spyder 3 line scan cameras that are

mounted at 120° intervals perpendicular to

the plane of the rolling steel shaft in protec-

tive enclosures around the output of the push

bench. In a former version of the system, two

powered 200mW 473 nm blue laser light sourc-

es from Laserglow Technologies (Toronto, ON,

Canada; www.laserglow.com) are employed

on both sides of each camera to illuminate the

surface of the steel with dark field lighting. As

a result of the geometry of the system, it is pos-

sible to capture a complete image of the tube

continuously and in real-time (Figure 2a and b).

Because of the temperature of the envi-

ronment, it was important to keep the cam-

eras cool continuously. To do so, compressed

cooled refrigerated air is injected into the pro-

tective enclosures to protect the camera and

laser equipment from the heat and the harsh

environment. Not only does the air cool the sys-

tems, but excess air is then expelled through a

window through which the lasers project their

light beam and the camera captures the image,

preventing the deposition of scale, oxides, dust

and liquids.

Figure 2 a and b: To enable the system to accurately capture a 360° image of the surface of the steel tube (3), the system uses three sets of lasers

(1) and 14.000 lines/s line-scan cameras (2). Figure 2b: Sets of lasers and cameras are mounted at 120° intervals in the same plane perpendicular to

the plane of the rolling shaft in protective enclosures around the output of the push bench.

Figure 3: Typical defects that occur in the steel include (from left): (a) material pasted (b) mate-

rial removed and (c) rolling marks.

1612VSD_25 25 11/30/16 11:48 AM

1.0

0.2 0.4 0.6

TNR (specificity) = 1 - FPRTNR (specificity) = 1 - FPR

thr:0.534

0.8

Threshold

TPR (sensitivity), TNR (specificity) vs. threshold

Rates

1.0

FPR = 1.58%FNR = 1.49%

0.8

0.6

0.4

0.2

0.0

TNR (specificity) = 1 - FPRTNR (specificity) = 1 - FPR

1.0

0.2 0.4 0.6

TNR (specificity) = 1 - FPRTNR (specificity) = 1 - FPR

thr:0.534

0.8

Threshold

TPR (sensitivity), TNR (specificity) vs. threshold

Rates

1.0

FPR = 1.58%FNR = 1.49%

0.8

0.6

0.4

0.2

0.0

TNR (specificity) = 1 - FPRTNR (specificity) = 1 - FPR

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m26

Industry Solutions Profile

Image processing

Once the images of the surface of the steel

are captured, they are transferred 100m to a

PC-based server in the control room over an

optical fiber Gigabit Ethernet link. Here, the

images are first pre-processed to enhance the

contrast of the images with custom built image

enhancement algorithms such as histogram

equalization. Since the usable data in the orig-

inal images are represented by close contrast

values, the technique increases the global con-

trast of the images.

Having enhanced the images, they are then

processed using custom built software which, in

a previous version of the system, employed an

assisted learning system based on Support Vector

Machines (SVMs). Once the system has been

taught to learn specific defects from different

examples by texture, contrast, and size, the algo-

rithm can then automatically detect and classi-

fy the most important production defects in the

production environment (Figure 3).

The PC-based server used to store the

images from the cameras together with data

of the defects found and their locations on the

tubes also stores alarms for pressure, tempera-

ture, speed signal, communications, and other

tube production data in an Oracle database for

quality control and traceability. It is also possi-

ble to perform remote inspection of the data on

the server by installing a client application on

a computer connected to the company LAN.

Since the system was originally developed,

it has undergone several enhancements. While

the basic concept behind the system has been

retained, much has been improved. The struc-

ture of the system has now been redesigned

to enable the alignment and the adjustment

of the cameras and the lighting to be adjust-

ed more easily.

Newer versions of the system have also adopt-

ed a liquid, rather than an air refrigeration tech-

nique to enable both the lighting and sensors to

be placed closer to the

steel tubing and to allow

hotter or larger steel sec-

tions to be imaged.

LED light sources from

Metaphase Technolo-

gies (Bristol, PA, USA;

www.metaphase-tech.

com) have also replaced

the earlier lasers, lead-

ing to an increase in life-

time of the light sources

from 2000 to 50,000

hours, and eliminating

artifacts such as speckle

that can corrupt the

images captured by

the cameras.

The software user interface has also been

improved, enabling plant operators to visual-

ize the position and the specific nature of the

defects on the steel as they occur (Figure 4).

It is now also possible to store months of pro-

duction data on the database, allowing plant

managers to review the periodicity of any errors

that might be occurring and to schedule regu-

lar preventative maintenance operations. The

system can also support many users who can

not only access the system locally but over the

Internet as well.

Change in classification

Perhaps the most important recent develop-

ment to the Surfin’ system, however, is the

replacement of the older SVM-based clas-

sifier by an in-house developed candidate

window detection stage and a Convolutional

Neural Network (CNN) for defect classifica-

tion. CNNs can learn to extract the relevant

features that characterize each type of defect

from the training images and perform classi-

fication, while an SVM only maps its input to

some high dimensional space where the dif-

ferences between the classes of defects can

be revealed.

By assuming that all objects of interest–such

as the defects–share common visual properties

that distinguish them from the background, the

Figure 4: A custom-built software user interface enables plant opera-

tors to visualize the position and the specific nature of the defects on

the steel in real time.

Figure 5: The most relevant performance

metric when performing 2-class classification

(as in defect versus no-defect) is the AUC,

or Area Under the ROC (Receiver Operating

Characteristic) curve. The better a model is,

the closer its AUC is to 1. In this way, when

comparing several models, the best one can

be selected by choosing the one with the

highest AUC. While the value of AUC with

the SVM classifier is 0.88, the AUC of the

CNN-Surfin classifier is 0.997 for the two class

classification case.

Figure 6: The point where the vertical line

corresponding to a threshold value cuts both

curves yields False Positive and False Negative

Rates. A common choice for the threshold

value is that which yields approximately equal

False Positive and False Negative Rates. For

CNN-Surfin, a False Positive Rate of 1.58%

and a False Negative Rate of 1.49% were

achieved.

1612VSD_26 26 11/30/16 11:48 AM

Thanks for a great 2016.

Season‘s Greetings and

a Happy New Year.

What you expect +more

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 27

Industry Solutions ProfileIndustry Solutions Profile

candidate window detection stage outputs a set of regions that are likely

to contain those defects. A Convolutional Neural Network (CNN) then

extracts the learned features and performs the actual defect classifica-

tion on the image data.

The CNN classifier was validated over a custom image database with

defective hot tube images, and it was discovered that the deep learn-

ing-based approach significantly outperformed the earlier SVM Classi-

fier by decreasing both the number of false positives and false negatives

that were detected.

The most relevant performance metric when performing 2-class clas-

sification (as in defect versus no-defect) is the AUC, or Area Under the

ROC (Receiver Operating Characteristic) curve, which is built by plot-

ting the False Positive Rate in the x-axis and the True Positive Rate in

the y-axis and then computing the area under this function (Figure 5).

Ideally, the value of this function is 1.00 for every value in the x-axis,

and thus the better a model is, the closer its AUC is to 1. In this way,

when comparing several models, the best one can be selected just by

taking the one with the highest AUC. While the value of AUC with the

SVM classifier is 0.88, the AUC of the CNN-Surfin classifier is 0.997

for the two class classification case.

In addition, for a given model, a threshold can be selected to enable the

system to decide if a sample is defective. Since the models’ output is nor-

mally a probability value between 0 and 1, a sample will be tagged as NOK

if the probability value is greater than the threshold, and OK otherwise.

By moving the threshold value towards 1.0, the number of false posi-

tives can be reduced at the cost of increasing the number of false nega-

tives, or vice versa. It is then possible to visually check where the system

operates by plotting the threshold in the x-axis and both the Specificity

or True Negative Rate (= 1 – False Positive Rate) and the Sensitivity or

True Positive Rate (= 1 – False Negative Rate) in the y-axis.

The point where the vertical line corresponding to the threshold

value cuts both curves yields False Positive and False Negative Rates.

A common choice for the threshold value is that which yields approxi-

mately equal False Positive and False Negative Rates. For CNN-Surf-

in’, a False Positive Rate of 1.58% and a False Negative Rate of 1.49%

were achieved (Figure 6) compared with a False Positive Rate of 17.98%

and a False Negative Rate of 18.00% on the SVM version of Surfin’, a

x12 decrease in the number of classification mistakes made by Surfin’.

The new classifier is now set to be implemented in production envi-

ronments. Even so, engineers at Tecnalia are working to improve the

system with the aim of enabling steel producers to produce steel with

zero defects. The 4-class problem (OK versus 3 types of defects), for

example, has been evaluated for CNN-Surfin’ using a generalization

of the AUC (an averaged extension) and it yielded AUC = 0.9956. More

samples, however, are currently being gathered to make this number

statistically significant.

Since its introduction, the Surfin’ system has been delivered to com-

panies such as Tubos Reunidos (Bilbao, Vizcaya, Spain; www.tubos-

reunidos.com) and Aceros Inoxidables Olarra (Loiu, Bizkaia, Spain;

www.olarra.com) where it has enabled production issues to be detect-

ed at early stages in the hot process production. Tecnalia is working

with other steel production companies to deploy the system to detect

more complex shaped steel parts, such as beams with U or H-shaped

cross-sections that are used in construction and civil engineering.

Tecnalia has formed a relationship with Sarralle Group (Azpeitia,

Gipuzkoa, Spain, www.sarralle.com) to distribute the Surfin’ system

worldwide.

Companies mentioned:

Aceros Inoxidables OlarraLoiu, Bizkaia, Spainwww.olarra.com

Edmund OpticsBarrington, NJ, USAwww.edmundoptics.com

Laserglow TechnologiesToronto, ON, Canadawww.laserglow.com

Metaphase TechnologiesBristol, PA, USAwww.metaphase-tech.com

Tubos Reunidos Industrial S.A.Bilbao, Vizcaya, Spainwww.tubosreunidos.com

Teledyne DalsaWaterloo, ON, Canadawww.teledynedalsa.com

TecnaliaDerio, Bizkaia, Spainwww.tecnalia.com

SarralleAzpeitia, Gipuzkoa, Spainwww.sarralle.com

1612VSD_27 27 11/30/16 11:48 AM

PRODUCTSVision+Automation

» E-mail your product announcements, with photo if available, to vsdproducts@pennwell.com | Compiled by James Carroll

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m28

Embedded computers MXC-6400 expandable embedded computers feature

6th generation Intel Core i7/i5/i3 processors and the

QM170 chipset. Targeting intelligent transportation

and industrial automation applications, the embedded

computers feature two DisplayPort and one DVI-I

ports enabling up to 4K UHD resolution, two

software-programmable RS-232/422/485 + two

RS-232 ports, three Intel GbE ports with teaming function, six USB 3.0 ports, and

16CH DI and 16CH DO. Additionally, the computers handle shock up to 50Gs.

ADLINK Technology, Inc., San Jose, CA, USA, www.adlinktech.com

Line scan infrared camera LineCAM12 features a 1024 x 1 InGaAs line scan

detector that is available with 250 µm tall pixels or

12.5 µm square pixels. The InGaAs array is backside

illuminated and has >75% quantum efficiency from

1.1 to 1.6 µm. The camera also operates in the SWIR

and visible spectrum from 0.4 – 1.7 µm acquiring

14-bit data at 37k lines/s on USB3 or Camera Link. The

camera is compatible with with C-, F-, and M42 mount lenses.

Princeton Infrared Technologies Inc.

Monmouth Junction, NJ, USA, www.princetonirtech.com

Backlights target industrial environmentsDesigned for inspection and measurement of fast moving objects, LTBP strobed

LED backlights feature uniformity down to ±10 %. Available in sizes rang-

ing from 48 x 36 to 288 x 216 mm, the lights come in red, white, green, and

blue models. These lights feature M8/M12 connectors, scratch-resistant protec-

tive covering, and a reduced thickness of 26 mm. Positioned behind the objects

to be inspected, the lights provide a silhouette, edge contrast and high illuminance with exposure times as low

as tens of μs. In addition to strobe mode, the lights work in continuous mode for alignment/setting when used with the

LTDV1CH-17V controller. Opto Engineering, Mantova, Italy, www.opto-engineering.com

First programmable USB 3.0 hub launchedThe USBHub3+ is an 8-port pro-

grammable USB 3.0 hub that is

reportedly the first programma-

ble USB 3.0 hub available. Up to

8 USB 3.0 ports can be controlled

through software to enable or dis-

able individual ports, set current

limits and monitor current and volt-

age on each port. An additional port

is provided to expand to multiple

hubs. Acroname’s BrainStem tech-

nology and API is used to control

the USBHub3+ and a sample open

source GUI is provided, but users can

also use C, C++, or Python to inter-

face with BrainStem APIs. Addition-

ally, the USBHub3+ is designed to

withstand up to +/-30kV ESD strikes.

Acroname

Boulder, CO, USA

www.acroname.com

1612VSD_28 28 11/30/16 11:50 AM

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 29

Vision ■+ Automation Products

Frame grabber features on-board 3D profilingThe Radient eV-CXP CoaXPress frame grabber,

the first in the Radient eV-Series line of frame

grabbers featuring on-board 3D profiling,

acquires from multiple independent cameras

at once by way of two (Dual) or four (Quad)

CXP connections, each supporting up to 6.25

Gbps of input bandwidth. The frame grabber

performs laser line extraction needed for 3D

profiling on the card itself, reducing system

demand and freeing resources for inspection

tasks. Capable of extracting 9,000 profiles

per second with no host CPU usage, the PCI

Express frame grabber is suitable for PCB, road

and rail maintenance, food analysis and other

inspection tasks.

Matrox Imaging

Dorval, QC, Canada

www.matrox.com/imaging

Camera features 12 MPixel Pregius sensorNewly available to the CX series of industrial

cameras is the VCXU-123M USB 3.0 camera

that features the monochrome Sony Pregius

IMX253 global shutter CMOS image sensor,

a 12 MPixel sensor with a 3.45 µm pixel size

that can achieve frame rates of 31 fps. Also

featuring low dark noise and a 71 dB dynamic

range, M3 mount, and 458 MB internal buffer

the camera measures 29 x 29 x 38 mm and

targets surface inspection, 2D/3D measure-

ment, package inspection and traffic moni-

toring applications.

Baumer

Radeberg, Germany

www.baumer.com

Camera features cloud-based data processingHyperspectral imaging camera manufacturer

Cubert and VITO’s Remote Sensing Unit jointly

developed the ButterflEYE-LS camera that fea-

tures a hyperspectral imaging chip from imec

and a 2 MPixel global shutter line scan Si

CMOS detector covering a spectral range of

470 – 900 nm at speeds of up to 30 fps. Addi-

tionally, the camera features a cloud-based

image processing solution developed by VITO

1612VSD_29 29 11/30/16 11:50 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m30

Vision ■+ Automation Products

Remote Sensing that is able to generate hyper-

spectral ground maps after completing a flight.

Weighing less than 400g, the compact camera

is suitable for deployment in small UAVs for

precision agriculture, vegetation, and environ-

mental monitoring.

Cubert

Ulm, Germany

www.cubert.org

IR cameras designed for outdoor useViento 67-640 infrared cameras, available in

9 Hz and 30 Hz models, are designed to be

deployed in rugged outdoor applications such

as surveillance or robotics. The cameras fea-

ture a 640 x 480 uncooled VOx microbolome-

ter infrared detector with a 17 µm pixel size and

provide standard NTSC/PAL composite analog

video output with simultaneous 8-bit / 14-bit

Camera Link digital output. Equipped with IP67-

rated environmental housing, the cameras fea-

ture a spectral range of 8 – 14 µm, fixed focal

length, fixed mount, automatic image normal-

ization with an integrated mechanical shutter,

and proprietary Image contrast enhancement

that offers heightened contrast and scene detail

in low thermal contrast settings.

Sierra-Olympic Technologies

Hood River, OR, USA

www.sierraolympic.com

USB 3.1 cameras feature Sony CMOS sensorsThese USB 3.1 cameras with Type-C connec-

tors are based on Sony CMOS image sensors.

The first models of the cameras—which will

be available in housed or single-board ver-

sions with different lens holders—include the

UI-3860LE camera, which is based on the Sony

IMX290 CMOS sensor. The IMX290 is a rolling

shutter, backside-illuminated 2 MPixel CMOS

sensor from the Sony STARVIS series that can

achieve a frame rate of 120 fps in full HD. Addi-

tionally, the UI-3880LE camera will be based

on the 6 MPixel Sony IMX178 STARVIS sensor,

which is a rolling shutter CMOS sensor capa-

ble of achieving speeds up to 60 fps. Future

models will include sensors from ON Semicon-

ductor, e2v, and more from Sony.

IDS Imaging Development Systems

Obersulm, Germany

www.ids-imaging.com

Cameras feature GenICam complianceA35 and A65 thermal imaging cameras target

machine vision and automation applications

and provide 14-bit temperature linear output

through GenICam-compliant software. The

A35 camera features a 320 x 256 uncooled

VOX microbolometer with a 25 µm pixel pitch

and 60 fps frame rate, while the A65 camera

features a 640 x 512 uncooled VOX microbo-

lometer with a 17 µm pixel pitch and 30 fps

frame rate. Both cameras feature a spectral

range of 7.5 – 13 µm and are available with 10

field of view options, from 8 to 90°, providing

users the option to pinpoint a single target or

monitor a large area. Additionally, both ther-

mal imaging cameras are GigE Vision compli-

ant and measure only 4.2 x 1.9 x 2 in.

FLIR

Wilsonville, OR, USA

www.flir.com

Microscope cameras feature USB 3.0 interfaceThe KAPELLA and RIGEL cameras are color

and monochrome versions, respectively, of

the same camera, which features a back-illu-

minated 2.3 MPixel Sony CMOS image sensor

with a 5.86 µm pixel size and can achieve a

frame rate of 60 fps. The PROKYON camera

features an image sensor with the same speci-

fications as the KAPELLA and RIGEL, but is able

to produce images with resolutions from 2.3

to 20.7 MPixels. All three USB 3.0 cameras fea-

ture 12 bit A/D conversion, a dynamic range of

73.3 dB, and are equipped with an Intel Quad

Core processor with 8 GB RAM.

Jenoptik Optical Systems

Jena, Germany

www.jenoptik.com

LIDAR sensor captures hi-res 3D imagesUsing Time of Flight distance measurement

with calibrated reflectivities, the Puck High-Res

LiDAR sensor targets applications ranging from

autonomous vehicles to surveillance. The puck

expands on the VLP-16 Puck, a 16-channel,

real-time 3D LIDAR sensor that weighs 830 g.

Featuring a 360° field of view (FOV) and 100 m

range, the sensor delivers a 20° vertical FOV for

1612VSD_30 30 11/30/16 11:50 AM

Multi Angle and Colour Direct Lighting

FIBS-i75-8 is designed with

8 rows of led with 4 colours

(White ,Green ,Blue, Red) and

4 angles (15°, 35°, 55°, 75°).

Each row can be individually

controlled to enhance image

colour and effect for inspection

requirements. It is offered in

full and semi-circle.

www.falcon-illumination.com/www.falcon-illumination.de www.phrontier-tech.com

PHORCE® USB 3.0

Fiber Extender

For long-distance Machine

Vision and video applications

• Extends SuperSpeed USB3.0

connections up to 300

meters through MM or SM

fiber cables

• Plug-and-play: no drivers

required

• Supports 5Gb/s transmission

bandwidth

• Provides USB bus power for

USB devices

• Available for 1-fiber, 2-fiber,

and CWDM connections

w w w . v i s i o n - s y s t e m s . c o m V I S I O N S Y S T E M S D E S I G N D e c e m b e r 2 0 1 6 31

A D V E R T I S E M E N T

Product Showcase

Vision ■+ Automation Products

a tighter channel distribution—1.33° between

channels instead of 2.00°, to deliver greater

details in the 3D image at longer ranges. Addi-

tionally, the sensor features a Class 1 Eye-safe

laser with a wavelength of 903 nm, a rotation

rate of 5 – 20 Hz, and an integrated web server

for monitoring and configuration.

Velodyne LiDAR

Morgan Hill, CA, USA

www.velodynelidar.com

Multi-camera solution controls up to four camerasEnabling the control of up to four cameras at

once is the Norite N-5A100. The system con-

sists of individual N-5A100 cameras, which fea-

ture the 5 MPixel PYTHON5000 CMOS image

sensor in a 29 x 29 x 43 mm format. Multiple

Norite N-5A100 cameras can be controlled from

one user interface, and up to four cameras can

be connected to one frame grabber. For devel-

opers of vision systems with multiple cameras,

including those needed for 3D or area of inter-

est applications, the N-5A100 cameras offer

reduced system complexity at 105 fps through-

put per camera via CoaXPress interface.

Adimec Advanced Imaging Systems

Eindhoven, The Netherlands

www.adimec.com

CoaXPress camera features 50 MPixel sensorFeaturing a 35mm full frame 50 MPixel elec-

tronic global shutter CMOS image sensor that

can produce 7920 x 6004 images at more than

30 fps is the Flare 50MP camera. The camera—

which is available in monochrome and color—

provides four CoaXPress digital video outputs

that enable high-speed data transmission at up

to 25 Gbps. Additionally, the camera features

a dynamic range of 60 dB, 8/10/12-bit pixel bit

depth, and GenICam or Flare Control software

for camera control.

IO Industries

London, ON, Canada

www.ioindustries.com

USB 3.0 camera features 29 MPixel CCD sensorFeaturing the 29 MPixel KAI-29050 CCD image

sensor, which is a 35 mm sensor with a fully

global electronic shutter, is the new Lt29059

USB 3.0 camera. The camera also features a

Canon EF lens mouth with fully-integrated con-

troller for auto focus/iris supported by Lumen-

era’s API, a zero-loss 256 MB RAM frame

buffer, binning and region of interest modes,

as well as a locking USB 3.0 connector.

Lumenera

Ottawa, ON, Canada

www.lumenera.com

1612VSD_31 31 11/30/16 11:50 AM

D e c e m b e r 2 0 1 6 V I S I O N S Y S T E M S D E S I G N w w w . v i s i o n - s y s t e m s . c o m32

Sales Offices

Advertisers Index

Advertiser / Page no.

This ad index is published as a service. The publisher does not assume any liability for errors or omissions.

Vision ■+ Automation Products

Board-level or industrial USB 3.0 camerasThe 27 series of USB 3.0 cameras features a number of new color

and monochrome, industrial and board-level models. The 5 and 10

MPixel cameras, for example, fea-

ture the Aptina (ON Semiconduc-

tor) MT9P006 and MT9J003 CMOS

image sensors, respectively, and

feature a compact design starting

at 30 x 30 x 10 mm. Additionally,

these cameras feature a free 1D and

2D barcode software development kit as well as software for on-screen

measurement and image acquisition. Drivers for LabView, HALCON,

MERLIC, VisionPro, DirectX, Twain, and NeuroCheck are also included

with the cameras.

The Imaging Source

Bremen, Germany

www.theimagingsource.com

Line scan cameras achieve high speedsThe SW-4000M-PMCL and SW-8000M-PMCL Sweep monochrome

line scan cameras feature 4K (4096) and 8K (8192) CMOS line scan

sensors, respectively, can reach scan rates of 200 kHz and 100 kHz.

The SW-4000M-PMCL

camera features a 7.5

µm pixel size, 30.72 mm

sensor scanning width,

and F-Mount of M42x1

mount, while the SW-

8000M-PMCL features a 3.75 x 5.78 µm pixel size, 30.72 mm sensor

scanning width, and F-Mount of M42x1 mount. In both cameras, 8

and 10-bit data output is handled via a Camera Link Deca interface.

JAI

San Jose, CA, USA

www.jai.com

3D sensors designed for small part inspectionGocator 2400 sensors, which are currently available in the Gocator 2410

and 2420 models, feature a 2 MPixel camera with up to 1940 points/pro-

file resolution. The blue-laser profiling sensors—which are designed for

electronics and small parts inspection—feature an X resolution of 6 µm

and repeatability down to 0.2 µm, as well as a field of view of up to 32 mm

and a measurement range of up to 25 mm. Additionally, the

3D smart sensors feature

a GigE interface, a speed

of 400 – 5000 Hz with

windowing, an embed-

ded processor, and IP67

industrial housing.

LMI Technologies

Delta, BC, Canada

www.lmi3d.com

Main Office 61 Spit Brook Road, Suite 401 Nashua, NH 03060 (603) 891-0123 FAX: (603) 891-9328

Publisher Alan Bergstein (603) 891-9447 FAX: (603) 891-9328 E-mail: alanb@pennwell.com

Executive Assistant Julia Campbell (603) 891-9174 FAX: (603) 891-9328 E-mail: juliac@pennwell.com

Digital Media Sales Operations Manager Tom Markley (603) 891-9307 FAX: (603) 891-9328 E-mail: thomasm@pennwell.com

Ad Services Manager Marcella Hanson (918) 832-9352 FAX: (918) 831-9415 E-mail: marcella@pennwell.com

List Rental Kelli Berry (918) 831-9782 FAX: (918) 831-9758 E-mail: kellib@pennwell.com

North American Advertising & Sponsorship Sales Judy Leger (603) 891-9113 FAX: (603) 891-9328 E-mail: judyl@pennwell.com

Product Showcase Advertising & Reprint Sales Judy Leger (603) 891-9113 FAX: (603) 891-9328 E-mail: judyl@pennwell.com

International Sales Contacts

Germany, Austria, Northern Switzerland, Eastern Europe Holger Gerisch +49 (0) 8801-9153791 FAX: +49 (0) 8801-9153792 E-mail: holgerg@pennwell.com

Hong Kong, China Adonis Mak 852-2-838-6298 FAX: 852-2-838-2766 E-mail: adonism@actintl.com.hk

Japan Masaki Mori 81-3-3219-3561 FAX: 81-3-5645-1272 E-mail: masaki.mori@ex-press.jp

Israel Dan Aronovic (Tel Aviv) 972-9-899-5813 E-mail: aronovic@actcom.co.il

Should you need assistance with creating your ad please contact:

Marketing Solutions Vice President Paul Andrews (240) 595-2352 Email: pandrews@pennwell.com

Allied Vision ..............................................................................CV4

Alysium-Tech GmbH .....................................................................27

Edmund Optics ............................................................................ 4

Falcon Illumination ......................................................................31

Imperx ....................................................................................... 16

Jargy Co. Ltd. ............................................................................. 29

Matrox Imaging ...................................................................... CV3

Photron ...................................................................................... 23

Phrontier Technologies ................................................................31

Point Grey ................................................................................CV2

Stemmer Imaging ......................................................................... 5

Vieworks ...................................................................................... 2

1612VSD_32 32 11/30/16 11:50 AM

The Wait Is Over New! Matrox Iris GTR

The Next-Generation Smart Camera from MatroxThe latest Matrox smart camera is smaller to fit in tighter spaces, faster to inspect more and handle higher production rates, and is easier on your projectbudget. Plus it can either run your own vision applications programmed using the field-proven Matrox Imaging Library (MIL) or be set up using the Matrox Design Assistant flowchart-based vision software.

Watch the Iris GTR videowww.matrox.com/irisgtr/vsd

1612VSD_C3 3 11/30/16 11:50 AM

Your image is everything

Choose the right CMOS camera. With the best CMOS advice.The Mako offers a wide variety of models with next-generation

CMOS sensors. But which one is right for you? Trust our imaging

experts to help you compare the differences and select the

perfect sensor for your application.

RIGHT

CAMERA

RIGHT

PRICE

Learn more about choosing

the right CMOS sensor at

AlliedVision.com/MakoCMOS

1612VSD_C4 4 11/30/16 11:50 AM