The Reaearch Of Vehicle Detection And Tracking Based On Vedeo Frequency

Effective and accurate detection and tracking of moving vehicles in video sequences is the key to modern intelligent traffic monitoring systems. Through summing up and analyzing the characteristics of existing methods in vehicle detection and tracking, this paper pays great attention to investigate the practical techniques for moving objects detection and tracking under the condition of a fixed CCD camera, including such techniques as automatic detection of moving objects, elimination of extra shadows of vehicles, tracking of moving vehicles, and so on. Because of the advantage of easily fixing, good reliability and abundant visible information, this system becomes the direction of the development of traffic control system and the research hot topic at home and abroad presently.The background subtraction is an important approach in video-based vehicle detection. The approach segments moving vehicles in the camera's field-of-view through the difference between a reference frame, called referenced background image, and the current input frame. In the process of video obtaining, outside environment variation such as little dithering of vidicon, slow variational daylight and the sway of tree will affect the precision of moving target detection. Aiming at this problem, the paper presents a method of background reconstruction, in which there are moving targets in scene. The background can be dynamicly updated. It can decrease the influence of outside environment variation and shorten the time of measurement.Characters matching to recognize the type of vehicles by edge or gray always have a large computation. This paper calculates the distance of Hausdorff between the Harris corner which need to be recognized and the three types of swatches. The two whose distance of Hausdorff is smallest could be judged as the same type. Experiments result shows that the method could get a high recognition precision and less time-consuming. At last, we measure the vehicle speed by Harris corner.Focusing on the problem caused by time-consuming computation and multi-vehicles occlusion in object tracking, this paper investigates the basic tracking method of moving vehicles based on the theory of Kalman filter. The moving model of vehicle is established from Kalman filter technique, and the position and edge of the vehicle are used for estimation and match of the tracking object in the consecutive frames. The experimental results show that the approach tracks the moving vehicle efficiently.The above algorithm has been realized by experiments. The experimental results show that the algorithm has the advantage of high precision and less calculation. It has a good practical value in toll stations on freeway, automatic charge parks and so on.