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.
Description:
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