Anuradha.S.G¹, K.Karibasappa²and B.Eswar Reddy³, ¹RYMEC, India, ²DSCE, India and ³JNTUA, India

Motion detection and object segmentation are an important research area of image-video processing and computer vision. The technique and mathematical modeling used to detect and segment region of interest (ROI) objects comprise the algorithmic modules of various high-level techniques in video analysis, object extraction, classification, and recognition. The detection of moving object is significant in many tasks, such as video surveillance & moving object tracking. The design of a video surveillance system is directed on involuntary identification of events of interest, especially on tracking and on classification of moving objects. An entropy based real-time adaptive non-parametric window thresholding algorithm for change detection is anticipated in this research. Based on the approximation of the value of scatter of sections of change in a difference image, a threshold of every image block is calculated discriminatively using entropy structure, and then the global threshold is attained by averaging all thresholds for image blocks of the frame. The block threshold is calculated contrarily for regions of change and background. Investigational results show the proposed thresholding algorithm accomplishes well for change detection with high efficiency.

Video Segmentation, Object Detection, Object Tracking, Video Surveillance, motion detection.