The Detection And Tracking Of Video Road Vehicles Based On OpenCV

Intelligent transport system is currently being studied and worldwide focused on in the area of world traffic transport. These years, the application of ITS brings great economical benefit to traffic transport,and it plays a more and more important role in road design,traffic surveillance and highway charge. In this paper,as a important part of ITS, video vehicle detection and tracking technology is researched. Compared with traditional vehicle detection mathods,video vehicle detection has a lot of advantages such as easy installation and maintenance,wide monitoring areas, and also through image analysis and processing it can obtain much useful traffic imformation, including the amount of vehicle in certain period , the position of vehicle at any moment,and so on.Detection and tracking of moving objects in image sequence is also the most complicated direction of computer vision and digital image processing techniques. It is a ample project that including video collection, digital image processing and application development.It's too complex for a engineer to accomplish all these works at the same time the stability, practicability and general availability is difficult to guaranteed. In this paper. OpenCV, which is developed by the visual interactivity group in Intel's microprocessor research Lab with C++ language is introduced. Its functions can be directly used in the video program for specific development projects.Presently,at the condition of complex weather change.large-scale,multi-objective circumstances, the movement of vehicles segmentation and testing results is not satisfactory. So an efficient and robust detection and tracking system is needed eagerly for these all. So, in this paper, a section of video is given,and used to detect the vehicle object and get surveillance result. Our researches are as mainly as follows:In this paper, the basic framework of object tracking of OpenCV is use to establish a multi-modules video vehicle detection and tracking system. The system is composed of foreground of moving vehicle detection module, blocks feature of moving vehicle detection module, blocks tracking module. In the part of detection module, an adaptive vehicle object detection method based on background subtaction is introduced, which can exactly detect vehicle object; in the part of tracking, we use shape and centroid tracking combined with Kalman filter to carry out vedio vehicle tracking.At last, we use this system doing a lot of experiment under various contexts, and the experiments results are well analysed. The results demonstrate that the system can do automatic vehicle detection and tracking with high real-time and moderate robustness. Since the software is written by VC++ 6.0 in the Windows operation system, so how to migrate to other systems or embedded system platform we develop this under windows platform, and further improve the versatility and robustness has become the focus of future research work.