Traffic Light Recognition using Image Processing Compared to Learning Processes

In this paper we introduce a real-time traffic light recognition system for intelligent vehicles. The method proposed is fully based on image processing. Detection step is achieved in grayscale with spot light detection, and recognition is done using our generic "adaptive templates". The whole process was kept modular which make our TLR capable of recognizing different traffic lights from various countries. To compare our image processing algorithm with standard object recognition methods we also developed several traffic light recognition systems based on learning processes such as cascade classifiers with AdaBoost. Our system was validated in real conditions in our prototype vehicle and also using registered video sequence from various countries (France, China, and U.S.A.). We noticed high rate of correctly recognized traffic lights and few false alarms. Processing is performed in real-time on 640x480 images using a 2.9GHz single core desktop computer.