Lane detection and tracking is a significant component of vision-based driver assistance systems (DAS). Low-level image processing is the first step in such a component. This paper suggests three useful techniques for low-level im- age processing in lane detection situations: bird's-eye view mapping, a special- ized edge detection method, and the distance transform. The first two techniques have been widely used in DAS, while the distance transform is a method newly exploited in DAS, that can provide useful information in lane detection situa- tions. This paper recalls two methods to generate a bird's-eye image from the original input image, it also compares edge detectors. A modified version of the Euclidean distance transform called real orientation distance transform (RODT) is proposed. Finally, the paper discusses experiments on lane detection and track- ing using these technologies.
['Ruyi Jiang', 'Mutsuhiro Terauchi', 'Reinhard Klette', 'Shigang Wang', 'Tobi Vaudrey']
Low-Level Image Processing for Lane Detection and Tracking