Owing to the problems of inter frame difference method cannot extract the entire target and most optical flow algorithms with computational time, poor real-time performance, a local optical flow constraint target extracting algorithm of Kalman filter based on background modeling is proposed. Firstly use Kalman filter method based on background modeling predict and update the background, then make Lucas-Kanade local optical flow algorithm search the background changing region, finally determine the gray contour, extract target. Compared with the classical algorithms, the simulation results show that new algorithm can extract the moving object quickly and accurately, and has better robustness to the environment changes and target circuitous movement.

According to the time and space distribution of the video sequence image motion vector and the fact that the horizontal component of the non-zero motion vector is often more than the vertical component, this paper presents a cross-diamond search algorithm for motion estimation based on projection from studying the pre-judgment zero motion vector, the starting point of search prediction, the movement type determinant, search strategy formulation and other aspects. The algorithm ensures the image quality basically unchanged. In this case, the search speed of the proposed algorithm speeds up 95-245 times than full search and 4-6 times than the fast motion estimation algorithm. The proposed algorithm has a strong real-time character and an easy hardware implementation.