Traffic sign recognition system (tsrs): Svm and convolutional neural network

Abstract

TSRS (Traffic Sign Recognition System) may play a significant role in the self-driving car, artificial driver assistance, traffic surveillance as well as traffic safety. Traffic sign recognition is necessary to overcome the traffic-related difficulties. The traffic sign recognition system consists of two parts—localization and recognition. In the localization part, traffic sign region is located and identified by creating a rectangular area. After that, in recognition part, the rectangular box provided the result for which traffic sign is located in that particular region. In this paper, we describe an approach toward the traffic signs recognition system. Here, we worked on 12 selected signs for traffic sign detection and recognition purpose. In this intention, we used a support vector machine (SVM) and convolutional neural network (CNN) individually to detect and recognize the traffic signs. We obtained 98.33% accuracy for SVM with an 80:20 train and test data ratio. On the other hand, the test result was 96.40% accurate for CNN.