A Traffic Sign Detection Technique Using Road Scene Images and GPS/GIS Information

With the advancement of computational intelligence, autonomous driving has become the future development trend of the automotive industry. Since the safety is commonly considered as the first priority of self-driving and driver assistance systems, the understanding of transportation infrastructure is an essential problem. In this paper, a technique for traffic sign detection and recognition is proposed. Different from the general image-based methods, we also incorporate the vehicle position and geographic information to improve the accuracy. Based on the approximate location of a traffic sign obtained from GPS and GIS, it can be used to increase the confidence level of network detection results. In the experiments, the training datasets are derived from Google Street View images and collected with an in-vehicle camera. The performance evaluation compared to the image-only methods has demonstrated the effectiveness of the proposed approach.