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IJSTR >> Volume 2- Issue 7, July 2013 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Optimization Of Frame Rate In Real Time Object Detection And Tracking

[Full Text]

 

AUTHOR(S)

Laxmi Agarwal, Kamlesh Lakhwani

 

KEYWORDS

Index terms: Absolute Frame Subtraction, Automatic Licensed Number Plate, Histogram matching, Kalman Filter, OTSU, Object Detection, Object Tracking.

 

ABSTRACT

Abstract: The paper focuses on the development of the optimization of real time object system which uses a static camera to capture the video frames and track an object. The work proceeds as: Matching of the histograms created for the frame, Absolute frame subtraction to build an optimized automated object tracking system. As the location of the object is detected, it is tracked by using discrete Kalman Filter Technique. Identifying the object entering the viewing range of the camera, this is done by histogram matching algorithm. To recognize the object OTSU segmentation is used. Since the frame occurrence rate is increased it can be used in automatic licensed number plate system recognition.

 

REFERENCES

[1]. TP Chen and Haussecker et al., “Computer vision workload analysis: case study of video surveillance systems,” Intel Technology Journal, vol. 9, no. 02, 2005.

[2]. F Porikli and O Tuzel, “Human body tracking by adaptive background models and mean-shift analysis,” IEEE Int. W. on Performance Evaluation of Tracking and Surveillance, 2003.

[3]. P.F Gabriel, J.G Verly, J.H Piater, and A Genon, “The state of the art in multiple object tracking under occlusion in video sequences,” Advanced Concepts for Intelligent Vision Systems,pp. 166–173, 2003.

[4]. Jaime Gallego, Montse Pardas, Jose-Luis Landabaso, “Segmentation and tracking of static and moving objects in video surveillance scenarios,” In Proc. IEEE International Conference on Image Processing (ICIP), San Diego (California, USA), October 2008.

[5]. Kar-Han Tan, Narendra Ahuja, “Selecting Objects With Freehand Sketches,” In Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2001.

[6]. Eric N. Mortensen1, William A. Barrett2, “Intelligent Scissors for Image Composition.” Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, pages: 191 -198, 1995

[7]. A. Monnet, A. Mittal, N. Paragios, and V. Ramesh, “Background modeling and subtraction of dynamic scenes”. In CVPR, 2003.

[8]. Otsu, N., "A Threshold Selection Method from Gray-Level Histograms," IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No. 1, 1979, pp. 62-66.