The Vehicle Flow Detection Method Based On Video

With the rapid development of national economy, it is growing for the car ownership,andit comes for all kinds of transportation problem. So it is very important to establish a kind of intelligent transportation system(ITS) which can realize real-time traffic information detection, sharing and communication.Video-based traffic parameter detection with the advantages of rich information, configuration flexibility and low cost. The main contents include:(1) the detection of regional settings and geometric correction. First, the video data is collected and processed, then the lane is set manually in the first frame of the video data to determine the detection area, and the geometric transformation is used to correct the target image.(2) the moving object detection algorithm is analyzed and improved. Comparative analysis of the traditional detection methods, according to the features of actual traffic scenes,the frame difference method and background difference method combined with the detection of moving objects, and through background modeling for real-time updates on the background, and the algorithm is improved, which makes the detection more complete and reliable and accurate.(3) the target feature extraction algorithm is analyzed and improved.From the detection area binarization extracting vehicle information and data flow image,determine the two-dimensional boundary of target region, and then based on the center of the target area rear to select the appropriate matching criterion and count the number of vehicles.Compared with the traditional algorithm, the algorithm not only has high efficiency, but also can realize the multi lane and cross lane count.Measured data show that: the algorithm related to this paper can accurately measure the traffic flow over time, and the actual measurement accuracy attains 95%. It can be used in the traffic information collection system of highway, national high way and city roads of an important region.