一种鲁棒的非平坦路面车道线检测算法

A Robust Algorithm for Lane Detection on Unplanar Road

  • 摘要: 提出了一种鲁棒的非平坦路面车道线检测算法. 给出一种简单的逆透视变换方法,该方法不依赖于摄像机参数,计算简便. 基于法向车道线模型研究了车道线的线特征提取方法,结合线特征的方向特性和强度信息,提出了改进的Hough变换车道线直线检测方法,有效提高了检测的鲁棒性和计算速度. 利用检测出的直线对车道线进行精确定位,采用加权最小二乘曲线拟合方法完整地提取出图像中的车道线. 实验证明,算法在弯道和非平坦路面上都能准确地提取出车道线,具有较强的鲁棒性.

     

    Abstract: A robust lane detection algorithm on unplanar road is proposed. First, a simple inverse perspective mapping method is provided, which is easy to compute and is independent of any camera parameter. Based on the lane model in the normal direction, the line features could be extracted. Then, considering the direction and strength information of extracted line features, the lane line detection could be realized by using improved Hough transform algorithm, which is robust and fast. The detected lane line is the basic lane pattern for further refining the lane points. Finally, the refined lane points are fitted by curves with a weighted least squares method. Experiments demonstrate that the proposed method can detect the lane precisely both on the curve and unplanar road with good robustness.

     

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