The Research On Video-based Vehicle Detection And Tracking Technology

With the rapid development of modern social-economic, the importance of effective urban road traffic management has become more and more notable in our daily life. Therefore, the deep research on urban transportation problems has very important practical significance. The research of ITS, intelligent transportation system, comes to an issue of consequence, and the effective detection and accurate tracking of moving vehicles are the core of this research. The traffic condition detection and information collection by computer vision system has become a hot topic in the field of ITS, in which the most basic issue is the detection and tracking of moving vehicles.This paper makes specific studies on video-based vehicle detection and tracking system, based on summary and analyzes the existing technology on vehicle detection and tracking, some improvements are given for vehicle recognition and tracking, and shadow elimination during vehicle recognition is studied. Experimental results indicate that our algorithm is effective.The main contents of this paper are organized as follows:1,Vehicle detection based on video sequence. In this section, we present an improved video-based vehicle detection process. Through analysis and comparison of existing detection methods, we reviewed vehicle-based commonly used video object extraction methods, including frame difference method, background difference method and edge detection method, focusing on segmentation algorithm based on region. The experiments show that the improved frame difference is effective.2,Vehicle tracking based on video sequence. In this section, this paper proposes an innovative region-based vehicle tracking algorithm. In region-based vehicle tracking, multiple features match is usually used to improve the matching accuracy. For simple and effective consideration, the proposed tracking algorithm is this paper selects the regional center location of mass and target size of the moving vehicle as the matching feature. Experimental results indicate that the algorithm is feasible and can apply to real-time environment. And the experimental results of tracking are satisfactory. 3,Shadow elimination during vehicle detection based on video sequence. In this section, we focus on shadow elimination, which is a key step, in video-based vehicle detection system. On analyzing the causes and characteristics of the shadow, with the comprehensive utilization of gray image and binary image after difference, we present a novel shadow detection and elimination algorithm based on the background. Experiments show that our algorithm can remove the shadow of moving vehicle effectively and still reserve majority of target information, which lay a stable ground for extracting moving vehicle target.