Lane Detection Based on the Random Sample Consensus

Abstract

In order to improve real-time and robustness of the lane detection and get more ideal lane, in the image preprocessing, the filter is used in strengthening lane information of the binary image, reducing the noise and removing irrelevant information. The lane edge detection is by using Canny operator, then the corner detection method is used in getting the Image corners coordinates and finally using the RANSAC to circulation fit for corners, according to the optimal lanes parameters drawing lane. Through experiment of different scenes, this method can not only effectively rule out linear pixel interference of outside the road in multiple complex environments, but also quickly and accurately identify lane. This method improves the stability of the lane detection to a certain extent, which has good robust and real-time.