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.
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Ran, F., Jiang, Z., Wang, T., Xu, M. (2013). A Study of Vision-Based Lane Recognition Algorithm for Driver Assistance. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_53
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DOI: https://doi.org/10.1007/978-3-642-38715-9_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38714-2
Online ISBN: 978-3-642-38715-9
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