一种基于Python的车道线检测算法分析

Study on a Lane Line Detection Algorithm Based on Python

阐述图像处理的方法实现车道线的自动检测,将连续的视频图像经过分帧处理,生成静态图片;其次将静态图片进行灰度化、高斯滤波,设定感兴趣的区域;再经过canny边缘检测、霍夫变换,检测出车道线;最后将检测出的车道线与原图叠加显示。根据实际道路视频测试,在直线车道线和弯道车道线两种情况下,检测算法具有较高的准确率。

This paper describes the method of image processing to realize the automatic detection of lane lines. The continuous video images are divided into frames to generate static pictures;Secondly,the static image is grayed, Gaussian filtered, and the region of interest is set;After canny edge detection and hough transform, lane lines are detected;Finally, the detected lane lines are superimposed with the original image. According to the actual road video test, the detection algorithm has high accuracy in both straight lane lines and curved lane lines.