基于Gabor滤波器的车道线快速检测方法

Lane line quick detection method based on Gabor filter

  • 摘要: 针对在全景相机获取到的高交通信息量的复杂场景下传统Canny算子很难实时且鲁棒地提取车道线特征的问题,提出一种基于Gabor滤波器的最优方向区间快速检测算法。首先利用同心圆环近似展开法将全景图像展开成矩形图像,然后对展开图像进行不同相位角的Gabor滤波处理,快速得到使车道线边缘清晰度达到最高的方向区间。在Canny算子检测边缘过程中,只对处于该区间内的边缘点进行非极大值抑制及进一步处理,实现车道线的快速检测。最后算法在实拍的500帧视频样本上进行测试,识别率优于94.2%。结果表明所提算法不易受复杂环境影响,可用性强,有效地提高了车道偏离预警系统的实时性与稳定性。

     

    Abstract: Aiming at the problem that it's difficult for traditional Canny edge detection operator to extract the lane line features robust in real-time in complex scenes of a large amount of traffic information, an improved method for the optimal direction interval quick detection based on Gabor filter was proposed. First, the panoramic image was expanded into a rectangular image by the concentric circle approximation expansion method. Then the expanded image was processed by Gabor filter with different phases, thus obtaining the direction interval which had the highest clarity of the lane line quickly. In the process of edge detection with Canny operator, only the edge points in the optimal interval were used for non-maximum suppression and further processing. Finally, the algorithm was tested on 500 real images for videos, and the recognition rate could be better than 94.2%. The results show that the proposed method is robust for complex environment and has strong feasibility, which can effectively improve the real-time performance and stability of lane departure warning system.

     

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