关键词: 线性判别分析（LDA）, 线段检测器（LSD）, 直线-抛物线模型, 车道线分类, 视频序列连续性

Abstract: A lane classification algorithm is presented. Firstly, LDA（Linear Discriminant Analysis） is adopted to convert road images to gray images directly, which can distinguish the lanes and roads better. Secondly, LSD（Line Segment Detector） is applied to detect straight lines of gray images to give the main direction of the lane by proper selection. On the basis of that, the pixels are selected within the grayscale range of the lane. Pixels in far vision are fitted by parabola while pixels in near vision use linear fitting. In the meantime, the lanes are marked by classification. Finally, the detecting results are verified by the continuity of video sequence. Experimental results show that the proposed method has good effects on the detection of curves and straight lines. The processing speed is 10 f/s while the frame rate of the original video is 15 f/s, which basically meets the real-time requirements.

Key words: Linear Discriminant Analysis（LDA）, Line Segment Detector（LSD）, linear-parabola model, lane classification, continuity of video sequence