面向复杂光照环境的车道线检测方法

Lane detection method for complex lighting environment

在复杂光照环境下由于光照不均匀,导致路面上的光照出现强弱不一的情况,使得车道线的亮度和颜色发生变化,从而对车道线检测造成困难。为了提高对车道线检测的精度,提出了一种面向复杂光照环境的车道线检测算法。算法主要以车道线的纹理特征为依据,借助投票算法对交通道路上的图像消失点位提取特征点,构建出车道线的关键检测区域;设计一种结合梯度和统计平均相对差的蚁群算法用于车道线边缘特征提取,并最终拟合标记出待测车道线。实验结果表明,所提方法在复杂光照环境下检测准确率高,鲁棒性强,显著改善复杂光照条件下的车道检测成功率。

Due to uneven lighting in complex lighting environments,the intensity of light on the road surface va-ries,resulting in changes in the brightness and color of lane lines,making lane line detection difficult.In order to im-prove the accuracy of lane detection,a lane detection algorithm for complex lighting environments is proposed.The al-gorithm is mainly based on the texture features of lane lines,and uses voting algorithms to extract feature points from the vanishing points of images on traffic roads,constructing key detection areas for lane lines;Design an ant colony al-gorithm that combines gradient and statistical average relative difference for lane edge feature extraction,and finally fit and label the lane line to be tested.The experimental results show that the proposed method has high detection accura-cy and strong robustness in complex lighting environments,significantly improving the success rate of lane detection under complex lighting conditions.