Robust and Real-Time Traffic Lights Recognition in Complex Urban Environments

The traffic lights play an indispensable role in urban road safety and researches on intelligent vehicles become more popular recently. In this paper an automatic system for robust and real-time detection and recognition of traffic lights for intelligent vehicles based on vehicle-mounted camera is proposed. The method applying image processing and pattern recognition theory mainly works in three stages. First, the candidate regions of traffic lights are extracted using the color threshold segmentation method. Secondly, noise removal and two types of filtering which take account of shape information are applied to the candidate regions. Thirdly, template matching using normalized cross correlation techniques is adopted to validate the traffic lights candidate. Experimental results show that the proposed algorithm works effectively and robustly for traffic lights recognition in complex urban environments.