Abstract
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 image processing in lane detection situations: bird’s-eye view mapping, a specialized 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 situations. 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 tracking using these technologies.
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Jiang, R., Terauchi, M., Klette, R., Wang, S., Vaudrey, T. (2010). Low-Level Image Processing for Lane Detection and Tracking. In: Huang, F., Wang, RC. (eds) Arts and Technology. ArtsIT 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11577-6_24
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DOI: https://doi.org/10.1007/978-3-642-11577-6_24
Publisher Name: Springer, Berlin, Heidelberg
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