Segmentation And Tracking Of Moving Object

The thesis is focused on the study of algorithm for moving target segmentation and tracking in video sequence images. Video sequence analysis is task-dependent. According to different applications, the corresponding algorithm will be selected. In this dissertation the theoretical model for the segmentation and tracking of the video moving object has been set up, which offers the mathematic description about the video moving object.In order to segment the moving objects from moving video background it is necessary to compensate the moving background. In this paper, we assume that the apparent background motion between two consecutive image frames can be approximated by affine transformation. In order to register the static background, we estimate affine transformation parameters using correlation-based block matching technique. Combine with inter-frame differential technique to get moving object region and a little noise. Then fill the line and row in the region, remove the noise through the area threshold. Combine with canny edge image to segmentation perfect moving object region.Method of Kalman filtering is discussed in terms of tracking moving object. Parameters of Kalman forecast are designed according to requirement of system and subsequently, system state vector, state transfer matrix and observation matrix are determined, and then tracking the trace of the moving object.