吉林大学学报(信息科学版) ›› 2015, Vol. 33 ›› Issue (4): 485-.

• 论文 • 上一篇    

基于双向窗口特征提取技术的车道线检测算法

范延军1,2, 张为公1   

  1. 1. 东南大学仪器科学与工程学院, 南京210096; 2. 中国计量学院计算机科学与技术系, 杭州310018
  • 出版日期:2015-07-24 发布日期:2015-12-02

Lane Detection Algorithm Based on Bi-Directional Sliding Window Feature Extraction Technology

FAN Yanjun1,2, ZHANG Weigong1   

  1. 1. School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China;2. Department of Computer Science and Technology, China Jiliang University, Hangzhou 310018, China
  • Online:2015-07-24 Published:2015-12-02

摘要:

为提高车道线检测算法的准确性与稳定性, 提出一种基于双向窗口特征提取技术的车道线检测算法。融合运用Hough 变换与边缘分布函数技术得到车道线的直线特征点; 运用双向窗口特征提取技术获得所有车道线特征点, 包括直线部分与弯曲部分。获得直线与双曲线相结合的车道线模型: 在近视场, 应用直线车道线模型能获得较好的鲁棒性; 在远视场, 使用双曲线模型可有效检测出车道线的弯曲部分。实验结果表明, 相较于已有的车道线检测算法, 该方法可有效提高多种场景下车道线检测的准确性和稳定性。

关键词: 车道线检测, 双向窗口特征提取技术, Hough 变换, 车道线模型

Abstract:

In order to enhance the accuracy and stability of lane detection, a lane detection algorithm based on bi-directional sliding window technology is proposed. Firstly, a combination of EDF(Edge Distribution Function) and Hough transform is used to obtain the linear models of lane boundaries. Secondly, bi-directional sliding window feature extraction technique is applied to detect real lane markings. Finally, a linear-hyperbolic lane model is used: in the near vision field, a linear model is used to obtain robust information about lane orientation; in the far vision field, a hyperbolic function is used, the curved parts of the road can be efficiently detected.Experimental results indicate that the proposed method can enhance the adaptability to deal with the random and
dynamic environment of road scenes, such as curved lane markings, sparse shadows, object occlusions and bad conditions of road painting.

Key words: lane detection, bi-directional sliding window feature extraction, hough transform, lane model

中图分类号: 

  • TP391. 41