An improved frame difference method for moving target detection

摘要

In this paper, we study the problem of moving target detection in video sequences. An improved frame difference target detection algorithm is proposed on the basis of the self updating average background model. By using numerical difference and logical operations between the average background and the current frame, the empty areas which are derived from traditional frame difference method can be extracted. For eliminating the isolated noise caused by background perturbation, this paper puts forward the neighborhood two values discriminant filtering method. Then, a compensation scheme based on the information of the empty areas together with the results of frame difference method is employed to make up the regions of moving object. Finally, simple comparisons between our algorithm and other methods are given. The experimental results show that the integrity of moving object extracted by our algorithm has been greatly improved than the frame difference method. Besides, in disturbance scene, it has better performance of disturbance rejection than the mixture of Gaussians model on the premise of guaranteeing the integrity of the moving target.