Visual surveillance has been a very active research topic in the last few years due to its growing importance in security, law enforcement, and military applications. The project presents moving object detection based on background subtraction for video surveillance system. In all computer vision system, the important step is to separate moving object from background and thus detecting all the objects from video images. The main aim of this paper is to design a bounding box concept for the human detection and tracking system in the presence of crowd. The bounding box around each object can track the moving objects in each frame and it can be used to detect crowd and the estimation of crowd. This paper gives the implementation results of bounding box for detecting objects and its tracking. In order to remove some unwanted pixels, morphological erosion and dilation operation is performed for object edge smoothness. The simulated result shows that used methodologies for effective object detection has better accuracy and with less processing time consumption rather than existing methods.

Input video, Frame separation, Background subtraction, Morphological Filtering, Performance measurement

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