Abstract
In this paper, we propose an integrated method for lane detection and vehicle detection, which tries to make a real-time analysis of vehicle video for identifying lane, detecting, and tracking forward vehicles. In lane detection, image preprocessing, line detection based on improved Hough transform, and straight-line model reconstruction are used. For vehicle detection, preprocessing, vehicle shadow merging based on the improved search algorithm, regions of interest (ROI) demarcation, lane determination, and vehicle tracking are used. The experiment results show that the time it takes to process an image is about 25ms. Additionally, the lane detection rate of vehicles driving on a structured road is approximately 98%, and the vehicle detection rate of the closest forward vehicle is approximately 81%.
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