Research And Implement The Algorithm Of Real-time Red Light Runners System Based On Video

With the rapid development of the world economy, the number of vehicles increase dramatically to lead to the traffic problem that is attented. Intelligent transportation system is born for solving this problem and now the global governments and relevant departments pay close attention to this new high-tech area. Automatic detection system of red light running vehicles with Video is an important component of the intelligent transportation system, in which an effective detection and real-time tracking are determine premise of behavior analysis and behavior judgment in vehicles.View as the above background, this paper studies detection and tracking of red light running vehicle algorithm. In basis of anglicizing and summarizing existing algorithms, it proposes two improved algorithms.Against the problem that the tradition background extraction method could not precise extraction background when moving objects have high density or appear too frequently. In this paper presented an algorithm of background reconstruction based on morphological and PIC (Pixel intensity classification). The algorithm classify the pixels in each frame into background area and moving objection area using three frame difference and Morphological analysis. Then extracting background modeling with PIC except the moving objection area, raised the frequency of background, so the background could be rebuilded proper. The experiment results show that the method proposed in this paper could extract accurate background in high vehicle density.In order to meet the requirements of real-time vehicle tracking, it designs an Mean Shift algorithm of automatic initialization window. Another in the cases of the similar of target color distribution and background, it considers the Mean Shift Algorithm will lose target. So, according to position information in front, kalman filter is used to predict the possible position of target image in the frame, and then at the location of the neighborhood you can use the Mean Shift to find the true target location. It enriches the use of known information and enhances the tracking results by the use of target movement information of before frame. Experiment verifies the effectiveness of the method.