White line detection for common roads by edge clustering using brightness gradient direction

Abstract

We propose image processing method for road white-line detection using brightness gradient direction of edges. Many methods for white-line detection have been proposed for standardized roads. These methods use model fitting for the detection of edges on white-line contour. So it is difficult to apply these methods to non-standardized roads for which modeling is difficult. To expand the scope of white-line detection to common roads in the future, it is necessary to achieve processing without models. Clustering based on position proximity of edges is one approach. However, there is concern about degrading noise reduction that has so far been done by model fitting. In this study, we developed an edge clustering method that utilizes the characteristics of edges on white-line contours; proximity of position as well as proximity of brightness gradient direction. In the proposed method, edges are first clustered based on proximity of gradient direction. And for each cluster, edges are again clustered based on proximity of position. Edge filter bank is specially designed for the first clustering and the effectiveness compared to conventional filter bank is explained. By applying the method to the images taken by on-board camera, we demonstrate that white-line detection that can apply to diverse road environments but is hardly affected by noise can be realized.