Statistical model-based change detection in moving video
Signal Processing
Machine vision
Digital Image Processing
Computer and Robot Vision
The MPEG-4 video standard verification model
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, an efficient moving object extraction algorithm for surveillance application is proposed which employ change detection strategy to obtain motion information of moving-object instead of complex operator. In addition, background subtraction is introduced to solve the problems of still object and uncovered background which is generally ill-inherency existed in conventional method. After that, the internal part region of moving-object may be confused with real-static region due to frame difference used. Hence, we use the concept of region adjacent graphic to overcome it. Finally, a post-processing step is used to remove noise regions and refine the shape of objects segmented. Moreover shadow effects can be suppressed in the pre-processing step. Experimental results demonstrate various results of segmented video sequence for both indoor and outdoor scenes and show that the proposed algorithm is superior to others in terms of obviating static region of internal part of moving-object and edge defects.