Robust lane recognition for structured road based on monocular vision

A robust lane detection and tracking system based on monocular vision is presented in this paper. First, the lane detection algorithm can transform raw images into top view images by inverse perspective mapping (IPM), and detect both inner sides of the lane accurately from the top view images. Then the system will turn to lane tracking procedures to extract the lane according to the information of last frame. If it fails to track the lane, lane detection will be triggered again until the true lane is found. In this system, θ-oriented Hough transform is applied to extract candidate lane markers, and a geometrical analysis of the lane candidates is proposed to remove the outliers. Additionally, vanishing point and region of interest(ROI) dynamically planning are used to enhance the accuracy and efficiency. The system was tested under various road conditions, and the result turned out to be robust and reliable.