Traffic Sign Detection and Recognition Method Based on Optimized YOLO-V4

Traffic sign detection and recognition is the core function of automatic driving system.In order to identify traffic signs in real time and accurately,a method is improved on the basis of YOLO-V4 and combined with the spatial pyramid pool(SPP) module.Firstly,to increase the resolution and receptive field,the resolution of the three scales of the original feature map is changed to 26×26 and 52×52.Then,SPP module is added to the connection layer to eliminate the constraints of the network on the fixed scale,obtain the optimal characteristics in the maximum pooling layer and improve the network performance.Experiment uses the tachograph to collect various traffic sign images,compared with other excellent methods,the proposed method achieves better performance.The average detection and recognition accuracy of the proposed method is 99.0%,and the average detection time is 0.449 s,which meets the requirements of real-time detection.