Moving Object Detection and Segmentation Based on Adaptive FrameDifference and Level Set

The adaptive frame difference method is used to detect moving objects in video sequences, in which two- or three-frame difference method is chosen to adjust the frame difference area automatically according to the changing trend of the frame difference area in order to prevent the loss of detected objects. Then the centroid position of moving objects is inferred according to centroid movement of frame difference region after post-processing using mathematical morphology on the frame difference image. A fitting ellipse which has same second-order central moments with the frame difference region is generated as the initial contour for the geodesic active contour (GAC) model. The level set function restricted by a nonlinear heat equation with normalized diffusion rate eliminates the time-consuming re-initialization procedure completely and reduces the number of iterations and the runnning time. Experimental results verify the effectiveness of the proposed algorithm.