Traffic Lights Detection and Recognition Based on Color and Shape with SVM

Abstract

Traffic signal lights recognition system is an essential part of Advanced Driver Assistance Systems (ADAS). Methods for traffic lights recognition based on single feature and fixed threshold filtering are usually ineffective in complex background and variable lighting environment. To solve this problem, an approach based on features combination of color and shape of traffic lights is proposed, and the method of machine learning is used for recognition of traffic lights. On the basis of extracting the characteristic parameters of the candidate region, the SVM classifier is constructed to classify the traffic signal lights. Experimental results show that this method can realize the accurate location and recognition of traffic lights in complex scenes.