Performance Evaluation of Integrated Lane Colorization Using Canny Edge Detector & Relaxed Median Filter

Abstract

Lane coloration has become popular in real time vehicular ad-hoc networks (VANETs). Automated road lane detection has been the crucial part of vision-based driver assistance system of intelligent vehicles. This driver assistance system reduces the road accidents, enhances safety and improves the traffic conditions. In this paper, presents an algorithm for detecting the lanes on the road with a view to the smart navigation of intelligent vehicles. So in order to reduce the limitations of the existing researchers we have proposed a new strategy which uses bilateral filter as preprocessing stage which has ability to reduce the noise from images before further processing. Firstly, it converts the RGB road scene image into gray image and filter using relaxed median filter. Then the gray scale image is scaled to particular level to obtain the binary image. Canny edge detector has been applied to outline the road lanes and colored. The proposed algorithm has been designed and implemented in MATLAB. By passing different images it has been shown the significant improvement of the proposed algorithm over the existing algorithms.