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The vision based Lane Departure Warning System (LDWS)is a effective way to prevent Single Vehicle Road Departure accident. In practice, a variety of complex noise make it very difficult to detect lanes fast and accurately, so to establish a set of image processing method which can give results fast and accurately in the non-ideal conditions is the primary work. In this paper, a lane detection method for Lane Departure Warning System is proposed. The Canny algorithm is determined as the edge detection method according to the experiment comparison, and Hough transform is selected as the efficient way to detect the beeline. To meet the real-time requirement, the region of interest (ROI) is defined to reduce noise for rising accurately, and to enhance the processing speed. At last, experiment results indicate that this lane detection method can extract lane information from road images acquired efficiently and accurately.