Traffic light detection and tracking based on Euclidean distance transform and local contour pattern

Abstract

This paper proposes a new recognition approach for traffic light based on Euclidean distance transform (EDT) and local contour pattern (LCP). There are two main contributions of this paper. First, this paper combines principle component analysis (PCA) with EDT-based image to detect traffic light colors. The color space for specific colors is partitioned more precisely, which leads to a high recognition rate. Second, we incorporate the above color detection into the contour segmentation of traffic light holder based on the LCP to further improve the recognition rate of traffic light. The experimental results show that our approach is able to detect traffic light far away from camera about 50-80 m and the average recognition rate can reach up to 99.29 %. © 2013 Springer-Verlag.