Research On Vehicle Flow Detection And Vehicle Tracking Algorithm Based On Video

With the social development and urban expansion, population increase, whilealso increasing the total number of vehicles, resulting in a traffic system pressurecontinuously increases. Therefore, the Intelligent Transportation System (IntelligentTransportation System, ITS) highlights the growing importance of research, its coreis video-based vehicle flow detection and vehicle tracking study. The main goal ofthis paper is based on machine vision technology to detect, identify, track the roadvehicles, and get vehicle flow statistics.The issue of moving traffic flow detection and vehicle tracking were studied,the existing detection and tracking technology were analyzed and summarized, andat the same time, based on research achievements at home and abroad, thecorresponding algorithms are optimized and improved. The specific studies are: thecollected video image is preprocessed, and using an improved background updatingalgorithm of Gaussian Mixture Model, that the current frame image subtracts thebackground image can obtain the foreground image(i.e. moving target image), thenprocess it using Otsu threshold segmentation method to extract the moving targetvehicle; then combine centroid-based feature matching and Mean-shift iterativealgorithm to track the extracted target; at the same time, count for each detectedtarget tracking chain to complete traffic flow statistics. In software, at the VisualStudio2005development platform, based on the MFC framework, using Open CVdata structures, functions, designs and achieves the system about vehicle flowdetection and vehicle tracking.On the basis of this algorithm, detect and track the two different angles ofvideo. This algorithm experimental results show that, the accuracy of vehicle flowdetection remained above ninety percent, with timeliness strong to track, and thesystem achieved the desired results, verified the stability of the algorithm.