Research on the Method of Traffic Signal Image Detection and Recognition

Abstract

Traffic lights play an important role in the distribution of conflicting traffic flow, and the correct detection and identification of traffic lights play an important role in reducing the occurrence of traffic accidents. Since the 1980s, China has begun the research and development of intelligent self-driving vehicles, which have higher requirements for all kinds of traffic sign recognition. Based on the above situation, this paper has done some research on traffic light image detection and recognition, which has far-reaching significance in the field of auxiliary driving and self-driving. The technical scheme adopted in this paper first uses the initial segmentation of RGB space and HSV color segmentation to get the selection of traffic lights, and then uses the lightweight network model to identify traffic lights and finally get the information of traffic lights. The experimental results show that the recognition accuracy and speed of this scheme can meet the requirements of the actual driving process.