The video coding standard MPEG-4 enables content-based functionality for various applications. To support this functionality and improve coding efficiency

MPEG-4 decomposes each frame of a video sequence into video object planes (VOPs). The technique is also used in content-based video retrieval and video monitoring system to improve intelligence degree; and its applications are extended to pattern recognition

computer vision et al. Thus

segmentation and tracking of video moving objects become a key related research topic. A novel algorithm for automatic segmentation and tracking of moving objects is proposed in this paper. On the base of different image

we utilize a method of combining Canny edge detection and fourth-orders statistic hypothesis testing in improving the moving areas separation results. Then we use region growing with color information in the moving areas to achieve precise boundary of moving objects; and make use of the last segmentation result

extract edge and color information of moving objects

apply edge model matching and color model matching approach to track the changes of moving objects

and detect temporarily still parts. The experimental results for several video sequences demonstrate that our approach is effective in precise segmentation and detect the temporarily still parts of the video moving objects.