Detection and classification of traffic lights for automated setup of road surveillance systems

Abstract

Traffic light plays an important role in controlling the traffic flow to maintain order. The state of the traffic light is used in automatic detection of illegal motions against traffic rules. In this paper, a video based-method is proposed to tackle the problem of detection and classification of traffic lights in the scenes, thus providing an automated setup of road surveillance systems in intelligent transportation systems (ITS). Firstly, the proposed method localizes the regions of traffic lights by detecting the regularity in which the traffic light colors change, and then classify the traffic lights by an SVM classifier on their shape features. This method is insensitive to illumination changing and adaptable to various kinds of shape settings. Finally, the experimental results show that this method is efficient and effective in automatically recognizing traffic lights.