Lane detection using inversion transform

Vision based lane detection is an essential task in both autonomous land vehicles research and active safety system development. The straight lines in the image are always corresponding to the lanes to be detected, especially in the near front of the vehicle. Thus Hough transform is employed to extract lanes form the edge map of the road scenes, plenty of linear structure staffs, however, may appear in the scene, therefore spurious peaks in the Hough space may exist which will lead to a incorrect detection. In this paper, we proposes a inversion transform based lane detection method, which first maps those distractive lines in the image into circles, while remains the linearity of the lanes to be extracted; then an improved parallel Hough transform is followed to detect these lanes. Experimental results illustrates that the presented method are both efficient and robust in lane detection.