SeePLANE

I-Cube

Presented byBarry T. Fryer

Dudley(MBA {IT};

MSc {Image Analysis}

Frame Work of Presentation

Introduction to IA / LPR (Theory)

SeePlane

Value proposition (3 options)

Over 1,000 OCR Systems in 30 CountriesOver 1,000 OCR Systems in 30 Countries

USA

Mexico

Colombia

Brazil

Portugal Spain UK Holland Italy Hungary Poland Kazakhstan Litha Israel

China

Hong Kong

Korea

Taiwan

Thailand

Singapore

Argentina South Africa (over 100 solutions) Australia

SeePlane: System descriptionThe system consists of cameras monitoring the

weigh bridge lane. All planes passing the cameras will be recorded in terms of the time, lane, direction, plane license number (if present), if allowed to use the lane (white list) and an alarm if the plane is either not allowed to take off or over weight (black list).

SeePlane: System operationThe OCR software allows PLANES to be enrolled

into a WHITE LIST, which are listed per trip. If an unauthorised OR OVER WEIGHT plane is detected this is recorded. If a plane in the BLACK LIST is detected, an alarm will be generated.

If TWO SYSTEMS ARE INSTALLED, the plane average speed will be determined, with an alarm for those above the set average speed.

Neural networksOperating in real time, are beingutilised extensively world wide.Here I-CUBE uses NEURALNETWORKS illustrates theconcept to automatically identify a plane. The ability to automatically predictand identify planes which are overweight orspeeding saves lives.

A Word About Our EyesEyes are very good contrast adjusters, but not good for distinguishing subtle variations in colorEyes can discern about 30 continuous levels of gray or color in a field of viewEyes are not good judges of distanceEyes cannot accurately reproduce measurementsEyes can not work in the dark or 24/7

SAME SIZE???

Why do Image Analysis?Improved Precision /Accuracy in MeasurementsReproducibility of ResultsHigher Throughput than Manual MethodsBetter Definition of Contrasting AreasMore Measurements / FasterReal Time Link to Databases

Vehicle:

• Size

• Colour

• Shape

• Texture

• Grey level

1 - Capture2 – Find plane number

3 – OCR4 – Report

OCR - 5 easy steps:

5 – Alarm if overweight or speeding !

Camera/IlluminationUnits

(Up to 6 per system)

IP orFrame Grabber

PLANE Software + DLL+Sample Client Program

PC Station

Included HardwareI/O Card +Terminal Block

Power Supply for SCH

Point A

Point B

PLANE SPEEDING SYSTEM

Configuration

Possible to have

multiple cameras to cover both

sides of the planes

Database remotely updated: Planes to

be expected

Automatic Database search

(local)

Recognition Rate: 0.2 sec

PLANE

• Size

• Colour

• Shape

• No of trips per day

• Etc

Additional items possibly captured:

Adapting Gigabit Ethernet for VisionStandard packet: 1440 Bytes (56 Bytes header)

”Jumbo” packet: Max. 16224 Bytes (one 56 Bytes header)

96.1% efficiency*

99,7% efficiency*

In combination with a High Performance Driver, based on TCP/IP offload-engine, it provides higher transmission efficiency and drastically reduces CPU usage.

(High CPU overhead for sending many small packets)

(Very low CPU overhead as only one packet)

*) Comparison based on sending 16224 bytes of data

Lens

Image sensor

Digitizing Pre-processing

Timing Interface

PLC

Cat-5eEthernet cableup to 100 m

Local I/Os:-Trigger input-Results output

Illumination control

Image Processing in

PC

Illumination

(Lens IrisVideo)

Power

Acquire

100110001010001110001010011100100100011101100011001010001000

PC

PC

Possible system configurations

Point-to-point(One camera, one PC)

GigESwitch

Many-to-one(Multiple cameras, one PC)

One-to-many (broadcast)(One or several cameras, with several PCs)

Control room monitoringControl room monitoring

Additional value for the airportAdditional value for the airport

OPTIONS?OPTIONS?Capital amount @ R390, 680.67

(Install and train on how to use)

Rental option @ R9, 761.16

(5 year period)

Cost per PLANE @ R39.04

(based on 250 planes a day)

ReferencesB.T. Dudley. "Image Analysis and Waste Technology in Africa", Binary - Computers in Microbiology, 5, 3-4. (1993) B.T. Dudley, A.R. Howgrave-Graham, A.G. Bruton and F.M. Wallis. "The application of digital image analysis to quantifying and measuring UASB digester granules", Biotechnology & Bioengineering. 42, 279 - 283. (1993) Castleman, K. R. 1998. Concepts in Imaging and Microscopy: Color ImageProcessing for Microscopy. The Biological Bulletin. 194 (2): 100-107.Russ, J.C. 1995. The Image Processing Handbook. 2nd ed. CRC Press. BocaRaton, FL.Inoue, S. (1986). Video Microscopy. Plenum Press Internet: www.I-Cube.co.za

Thanks to:

Barry T. DUDLEY(MBA {IT}; MSc {Image Analysis}; BSc {Brewing}; BSc Hons {Waste Technology})

ASD (Average Speed Determination) http://www.i-cube.co.za Cell: +27 (0) 82 562 8225MADADENI PH +27 (0) 31 764-3077

82 Kloof Falls Rd Fax 0866539659Kloof, Durban, Kwa-Zulu Natal, 3610, South Africa E-mail: ASD@I-Cube.co.za

“..any sufficiently advanced technology is indistinguishable from magic.” Arthur C. Clark

Technical QUESTIONS: