Synopsis

on

“SMART CAMERA”

Submitted in Partial Fulfillment of the Requirement for the Award of Bachelor of

Technology Degree in Electronics and Communication Engineering

Submitted By:-

Manpreet Singh(2309232)

Submitted to:-

Department of Electronics and Communication Engineering,

Ambala College of Engineering and Applied Research, Devsthali, Near Mithapur, Ambala-

133001

(Affiliated to Kurukshetra University, Kurukshetra)

(2013)

ABSTRACT

Smart cameras are rapidly finding their way into intelligent surveillance systems. Recognizing

faces in the crowd in real time is one of the key features that will significantly enhance

intelligent surveillance systems.

The main challenge is the fact that the enormous volumes of data generated by high resolution

sensors can make it computationally impossible to process on mainstream processors. For

security,such systems are usually installed in areas where crime can occur such as banks and car

parks.

The difference between digital cameras and smart cameras is that digital cameras just capture

images but smart cameras capture high level descriptions of the scene and analyze what they see.

For detection and recognition we use both low level processing and high level processing

algorithms. Smart camera architecture is described whereby a combination of an on-board

microprocessor and PLD’s allow for the embedding of image processing algorithmsin the

camera.

INTRODUCTION

A smart camera performs real-time analysis to recognize scenic elements. Smart cameras are

useful in a variety of scenarios: surveillance, medicine, etc. Trimedia processor. Our

system can recognize ge s tu r e s a t t he r a t e o f 20 f r ames / s econd . A "smart camera" is

basically a video camera coupled to a computer vision system in a tinypackage. This communication

begins stating the main differences between smart cameras and standard smart vision

systems. Smart camera architecture is described whereby a combination of an on-board

microprocessor and PLD’s allow for the embedding of image processing algorithmsin the

camera. A static thresholding algorithm is presented which demonstrates the ability

totrack non-uniformity in the inspection target. Finally, a prediction is made of

technological and applicational future evolutionon smart cameras.T h e s m a r t c a m e r a – a

w h o l e v i s i o n s y s t e m c o n t a i n e d i n o n e n e a t h o u s i n g – c a n b e

u s e d anywhere, in any industry where image processing can be applied. Companies no longer

need acabinet in which to keep all their computing equipment: the computer is housed within the

smartcamera. In the pharmaceutical industry and in clean rooms – when not even dust is allowed

– thiscan be a big advantage. A single square meter of space can be comparatively very

expensive – if there is no need for a component rack or cabinet, simply a smart camera, and then

this could savea lot of money. In particular, there would not be the usual cabling

involved for other visionsystems, and set-up is simple. Later in this communication are stated

some advantages of usingsmart cameras or PC-based systems in vision applications.In usual

vision systems scenarios, only a small fraction of a picture frame will be the region of  interest

(ROI). In fact, often no visual image of the ROI is even required. What if all that pixel pre-

processing and decision-making could be done within the camera? If allthe processing were done

inside the camera, the blob analysis of a gigabit image might result inonly a few hundred

bytes of data which need to be sent somewhere. Such compact packets of  data could

be easily transmitted directly to a machine control without even passing through a

PC.Information should be processed where the information occurs – i.e. the brain should be

behindthe eyes!The answer to the problem stated earlier is a stand-alone, smart camera.

LITERATURE SURVEY

This literature review provides a discussion of areas related to the qualitative research

undertaken by me. The majority of these areas have been selected primarily in line with a need to

position smart cameras within the wider context of historical, present and future considerations.

Other areas were selected for discussion because of a need to highlight their importance and

identify areas that require particular attention in order for smart cameras developments to cater to

the needs of particular audiences, an example of this in particular is the area of hd recording.

The idea to this project initially was gathered from an advertisement on television showing a

smart camera named “Samsung Galaxy Camera”. Detailed study and references were taken

from various sources including web articles.

A white paper titled “10 Truths About Smart Cameras” by Matrox Imaging was thoroughly

studied and referenced.

Other web articles that were studied are provided in the refrences column at the end of this

synopsis. The major website that was referenced was “www.samsung.com” .

MERITS AND DEMERITS MERITS

Cost - Smart cameras are generally less expensive to purchase and set up than the

PCbased solution, since they include the camera, lenses, lighting (sometimes),

cabling and processing.

Simplicity - Software tools available with smart cameras are of the point-and-

click variety and are easier to use than those available on PC's. Algorithms come

pre-packaged and do not need to be developed, thus making the smart camera

quicker to setup and use.

Integration - Given their unified packaging, smart cameras are easier to integrate

into the manufacturing environment.

Reliability - With fewer moving components (fans, hard drives) and lower

temperatures, smart cameras are more reliable than PC's.

DEMERITS

Security : Due to inclusion of an operating system and many applications one’s

security and privacy can be compromised.

Sluggish : Due to multiple applications running at the same time a smart camera

may be sluggish sometimes.

APPLICATIONS

Smart cameras can in general be used for the same kind of applications where more

complexvision systems are used, and can additionally be applied in some

applications where volume, pricing or reliability constraints forbid use of bulkier devices and

PC's.Typical fields of application are:

•Vision-based smart environments.

•Surveillance and tracking applications.

•Applications based on fusion of visual and other sensory data.

•Multi-view vision for Human-Computer Interfaces (HCI).

•3D scene analysis with distributed sensors.

•Distributed multimedia and gaming applications.

•Automated inspection for quality assurance (detection of defects, flaws, missing parts...)

• Non contact measurements.

•Code reading and verification ( barcode,Data Matrix, alphanumericetc.)

CONCLUSION

In contrast to common digital cameras, as known for example for taking holiday pictures, Smart

C a m e r a s a r e e q u i p p e d w i t h a c o m p u t i n g u n i t t h a t i s u s e d f o r t h e

a n a l y s i s o f c a p t u r e d images.

Recent advances in the research field of Computer Vision allow for the detection

of human faces and gestures and for the measurement of distances between objects. In future,

SmartCameras will be able analyse and understand scenes they observe in a cooperative

manner.Distributed Smart Cameras can be connected to each other by ad-hoc or infrastructure

networks

REFERENCES

[1] Web Article, “Smart Cameras in Embedded Systems”,

https://docs.google.com/document/d/1yG7er7labe7csErfu7vnPpoA1AeBirQGlnbDz9XO-

zQ/edit

[2] “Smart Camera”,

http://en.wikipedia.org/wiki/Smart_camera

[3] “Smart cameras : A Review”,

http://www.nicta.com.au/__data/assets/pdf_file/0004/16456/smart_camera_review.pdf

[4] “Smart Cameras - A complete vision system in a camera body, Vision Components”,

http://www.is.irl.cri.nz/products/smartcam.html.