Detection of lane line based on robert operator

Abstract

As autonomous driving technology becomes more and more popular, its safety is also attracting attention. Regarding the automatic driving of vehicles, the detection of road markings is particularly important. This paper improves the lane edge detection part of the Hough transform lane line detection method. Because the traditional Canny operator edge detection method is good for image processing, but the detection time is long, this paper replaces the Canny algorithm with the Robert operator edge detection method. The sub-edge detection method can improve the detection speed of lane line extraction. In MATLAB, by using multiple edge detection operators to perform edge detection on the same image 100 times, and taking the average of the detection time, it is found that the Robert operator takes a shorter time in the detection process than the Canny operator; Then the Robert operator and Canny operator are respectively fused into the Hough transform lane line detection. After 100 times, the same image is detected, and the running time is statistically averaged for comparison and analysis. The Robert operator is better than the Canny operator. The time taken is reduced by 0.15191 s. The simulation results show that the integration of Robert operator in Hough transform lane line detection improves the real-time performance of lane detection.