Lane Detection Using Edge Detection and Spatio-Temporal Incremental Clustering

Nowadays, research on intelligent vehicle technology is widely brought out. One of the most important functions that must exist on the intelligent vehicle is lane detection. The purpose of the lane detection system is to alert the driver if the vehicle is moving too close to lane boundaries, such as a white line. However, not all roads have been equipped with white lines as the lane boundaries. In this study, a method to detect lane boundaries on roads that do not have white lines as the road boundaries are proposed. Canny edge detection and Hough transforms are used to extract the lane boundaries, then cluster the result using spatio-temporal incremental clustering. The output of this method is an image with lines that represent the lane boundaries. This method can detect 90% road boundary of 1193 straight road images correctly.