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Proceedings Paper

Lane detection based on color probability model and fuzzy clustering
Author(s): Yang Yu; Kang-Hyun Jo
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Paper 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.

Paper Details

Date Published: 10 April 2018
PDF: 6 pages
Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061508 (10 April 2018); doi: 10.1117/12.2302941
Show Author Affiliations
Yang Yu, Univ. of Ulsan (Korea, Republic of)
Kang-Hyun Jo, Univ. of Ulsan (Korea, Republic of)


Published in SPIE Proceedings Vol. 10615:
Ninth International Conference on Graphic and Image Processing (ICGIP 2017)
Hui Yu; Junyu Dong, Editor(s)

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