Lane detection based on color probability model and fuzzy clustering

Yang Yu; Kang-Hyun Jo

doi:10.1117/12.2302941

10 April 2018 Lane detection based on color probability model and fuzzy clustering

Yang Yu, Kang-Hyun Jo

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061508 (2018) https://doi.org/10.1117/12.2302941
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

In the vehicle driver assistance systems, the accuracy and speed of lane line detection are the most important. This paper is based on color probability model and Fuzzy Local Information C-Means (FLICM) clustering algorithm. The Hough transform and the constraints of structural road are used to detect the lane line accurately. The global map of the lane line is drawn by the lane curve fitting equation. The experimental results show that the algorithm has good robustness.

Citation Download Citation

Yang Yu and Kang-Hyun Jo "Lane detection based on color probability model and fuzzy clustering", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061508 (10 April 2018); https://doi.org/10.1117/12.2302941

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