Research on recognition method for shady and broken lane
一种阴影及破损车道线识别方法研究

In order to meet the requirements of the adaptability of shady, broken and stained lane mark identification, this paper proposed a novel and effective lane mark identification algorithm. Turning the color image into gray scale and filtering out noise by median filter were introduced firstly. Then, it extracted feature of the lane by using the method of symmetrical local threshold segmentation and the result was contrasted with the classic segmentation method. Lastly, considering the distribution of feature points, it put forward the identification algorithm based on the improved RANSAC algorithm, and the validity of which was verified experiments using several videos, which were collected from common road and highway. The results indicate that, even for the lane mark which is blocked by shadows completely, broken seriously or covered by a large area of stains, it can be recognized accurately by using the improved RANSAC algorithm.