Lane Detection based on Color Probability Model and Fuzzy Clustering

机译：基于颜色概率模型和模糊聚类的车道检测

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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.

机译：在车辆驾驶员辅助系统中，车道线检测的准确性和速度是最重要的。本文基于颜色概率模型和模糊局部信息C均值（FLICM）聚类算法。使用霍夫变换和结构道路的约束条件来准确地检测车道线。车道线的全局图由车道曲线拟合方程式绘制。实验结果表明，该算法具有良好的鲁棒性。

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《International conference on graphic and image processing》|2017年|1061508.1-1061508.6|共6页
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Yang Yu; Kang-Hyun Jo;
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Inverse perspective mapping; Color probability model; Fuzzy local information C-means; Lane line detection;

机译：反透视映射;颜色概率模型;模糊的本地信息C-均值;车道线检测;

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3. An improved two-lane cellular automaton traffic model based on BL-STCA model considering the dynamic lane-changing probability [J] . Xiang Zheng-Tao, Gao Zhan, Zhang Tao, Soft computing: A fusion of foundations, methodologies and applications . 2019,第19期

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4. Lane Detection based on Color Probability Model and Fuzzy Clustering [C] . Yang Yu, Kang-Hyun Jo International Conference on Graphic and Image Processing . 2017

机译：基于颜色概率模型和模糊聚类的车道检测
5. Semantic Segmentation and Object Detection Based On Active Contour Model and Fuzzy Clustering. [D] . Memar Kouchehbagh, Sara. 2016

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6. Road Lane Detection Robust to Shadows Based on a Fuzzy System Using a Visible Light Camera Sensor [O] . Toan Minh Hoang, Na Rae Baek, Se Woon Cho, 2017

机译：基于可见光摄像机传感器的模糊系统对阴影的鲁棒车道检测
7. Preprocessing Technique for Lane Detection Using Image Clustering and HSV Color Model [O] . Na-Rae Choi, Sang-Il Choi 2017

机译：使用图像聚类和HSV颜色模型的车道检测预处理技术

Lane Detection based on Color Probability Model and Fuzzy Clustering

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