Motion Area Division Method Based on Normal Component of Edge Optical Flow

To lessen the accuracy demand of traditional motion area division methods, a motion segmentation algorithm based on normal component of optical flow is proposed. Edge-discriminating same area decision function is used to give out the relevance measurement between each edge point and its surrounding area, which is the base for further clustering. Simulation on both synthesized and real image sequences was made. It is proved that under appropriate selection of parameters, the novel algorithm can give correct division result. Moreover, compared to those methods using complete optical flow vector, the new method costs less time because that only normal component of the edge point' optical flow is evolved in the algorithm.