Research on Lane Detection Algorithm Based on Wavelet Analysis and Hough Transform

Lane detection technology is of great significance in intelligent transportation. Standard Hough transform is easy to generate false peak value and to cause error detection of line when extracting line. In this paper, the wavelet algorithm is combined to extract the area of interest in lane line recognition, and then the wavelet reconstruction and Canny algorithm are used to obtain the image edge, and the lane line is detected by the Hough transform algorithm based on linear parameter space reduction. This algorithm can improve the correct detection rate of lane lines, avoid the interaction between lane lines and reduce the misdetection of both sides of the lane. The improved algorithm is more conducive to the real-time control of intelligent vehicle assistance and automatic driving in time.