Abstract
In this paper, a real-time lane detection algorithm based on vision is presented. This algorithm improves the robustness and real-time of processing by combining with the dynamic region of interest (ROI) and the prior knowledge. When the lanes detected from previous frames have little changes for several frames, we recognize the lane only in dynamic ROI. We also proposed an erosion operator to refine the edge and a Hough transform with a restrict search space to detect lines with a faster rate. Experiments in structured road showed that the proposed lane detection method can work robustly in real-time, and can achieve a speed of 30ms/frame for 720×480 image size. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Ran, F., Jiang, Z., Wang, T., & Xu, M. (2013). A study of vision-based lane recognition algorithm for driver assistance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7929 LNCS, pp. 445–452). Springer Verlag. https://doi.org/10.1007/978-3-642-38715-9_53
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