基于改进简单图像统计算法的车道线识别

摘要

To reduce the false positive rate of the lane recognition algorithm in different road circumstances such that the lane is prone to the occlusion of shadow and the pavements appear in blanch.A lane recognition algorithm based on improved SIS threshold algorithm was proposed.The improved SIS threshold algorithm was used to transform the image data into binary data,during the image preprocessing stage.The line segment detection (LSD) algorithm was applied to detect whether there exists straight line in the image.The parallel lines were used to estimate the position of the vanishing point,which in turn eliminated the interference.The location of the lane line was determined in the lane line region of interest accurately through the analysis of the continuity of lane line and the values of lane spacing.Experiments were carried out on the video collected by the urban road and highway.The results show that the algorithm has low false positive rate and high robustness.The lane line can be identified precisely and quickly in the complex environment.%为降低车道线识别算法在车道线存在阴影遮挡、路面出现泛白现象等不同道路环境下的误检率,提出一种基于改进简单图像统计(SIS)阈值算法的车道线识别算法.在图像预处理阶段采用改进的SIS阈值算法进行二值化;采用直线段检测(LSD)算法检测直线,通过平行线对估计消失点位置,利用消失点去除干扰;利用车道线连续性和车道间距确定车道线感兴趣区,精确确定车道线位置.分别对在城市道路和高速公路上采集的视频进行实验,实验结果表明,该算法误检率低,鲁棒性高,能在复杂环境下快速、准确识别车道线.