Abstract: The existing lane detection algorithm mainly used edge information to extract lane features， and the algorithm that generated feature points through the contrast of adjacent pixels was easily affected by many external factors， and the detection results were easily disturbed， thus a new feature extraction algorithm was proposed. This algorithm improved the robustness of the algorithm in complex situations by calculating the tensor rotation of the gray structure in the region and selecting the largest changing trend pixel as the feature point. A new lane line feature extraction algorithm was used to extract feature points in interest areas， then feature points were selected， and Hough transform was used to fit them. After the lane lines were obtained ， the dashed line and the solid line were distinguished by the coordinate variances of the feature points. The algorithm was tested by driving pictures of about 15 500 frames in different time periods. The results show that the detection method may detect the lane line well under various environments， the correct rate under the sunny conditions is as 99.18%， the correct rate under the rainy conditions is as 97.19%， and the correct rate under the worn pavement conditions is as 94.72%，the correct rate under the night conditions is as 97.62%.

Key words: feature point, Hough transform, ridge algorithm, dashed line and solid line

摘要：

关键词: 特征点, Hough变换, 脊度量算法, 虚实线