Traffic Video Based Cross Road Violation Detection and Peccant Vehicle Tracking

For the requirement of monitoring cross road violation in intelligent traffic system, a method to recognize and track the peccant vehicle is presented. The static background is modeled by mixture Gaussian model, and the location of lane line is detected by Hough transformation, thus, coordinated series can be obtained from the monitor image. Information of vehicles can be obtained by background-frame binary discrete wavelet transforms (BDWT) method, and according to the distance between the vehicle and line, the peccant vehicle can be detected. An improved mean-shift method is used to track the peccant vehicle, and a close range camera is used to snapshoot the license plate according to the center of tracking window. Actual road tests show that the work efficiency of this method is high, and the accuracy is up to 80%; run-time of mean-shift tracking system is about 0.085s for each frame. So it has a certain practical value in the field of intelligent traffic.