An Image Processing Approach to Detect Lanes, Pot Holes and Recognize Road Signs in Indian Roads

Abstract

Most of the Indian rural and sub urban roads are not ideal for driving due to faded lanes, irregular potholes, improper and invisible road signs. This has led to many accidents causing loss of lives and severe damage to vehicles. Many techniques have been proposed in the past to detect these problems using image processing methods. But there has been little work specifically carried out for detecting such issues of Indian roads. To address this acute problem, the study is undertaken with the objectives like, to make a survey of Indian roads, to suggest the method to detect lanes, potholes and road signs and their classification and to suggest automated driver guidance mechanism. In this regard, Hough Transformation method is adopted for Lane detection, where as Color Segmentation and Shape Modeling with Thin Spline Transformation (TPS) is used with nearest neighbor classifier for road sign detection and Classification. Further, K-means clustering based algorithm is adopted for pothole detection. Therefore, the attempt is made to invent an automated driver guidance mechanism to make the driving safe and easier in Indian roads. The experimental results obtained are tested with real time image database collected across different roads in sub-urban areas in India and found satisfactory.