A Self-Adaptive Dynamic Window Method for High Speed Lane Detection

In order to improve image processing speed for lane detection in structured road, an algorithm with monocular vision self-adapting dynamic window is proposed. Grids are used to mark off the region of interest in the initial image. Then all the pixels are eliminated except those on the intersections of the grid lines, and feature pixels of the lane border in these intersections will be used to generate some dynamic windows using a dilatation algorithm. Then graying, median filtering, edge enhancement, threshold are used to process images in these dynamic windows to obtain lane board feature. At last, lane line can be fitted by Hough transformation. Experiments in structured road showed that the speed of image processing reached about 22ms/frame and the proposed algorithm could meet real-time request of the high speed vehicle vision navigation system.