An Efficient Method of Lane Detection and Tracking for Highway Safety

Abstract

Lane detection and tracking in highway road is one of the most crucial tasks for advanced driver assistance systems (ADAS). Advanced driver assistance systems are being developed to assist driver in driving process reducing road accidents. In this paper we present efficient lane detection and tracking method in highway roads. To do this, the first step is camera calibration used to remove the effect of lens distortion. Next canny edge detection algorithm finds the edges of the images. Then an adaptive region of interest (ROI) is selected. The ROI is actually based on the triangular shape appeared at the bottom of the image. ROI removes the unwanted region. After that possible lane markings are identified using Hough transformation analysing lane candidate pixels. Once the lane candidate pixels along with the lane are found, these pixels are continuously scanned to obtain the best fit using linear regression analysis. The system has been investigated under various illuminations in highway roads for detecting lane marking. The experiment shows that the proposed method can detect the lane quickly and accurately.