A CNN-based Traffic Sign Recognition System

The objective of this chapter is to detect and recognize the traffic signs using two methods. Traffic signs are silent speakers to the road users. It gives advance information about road conditions ahead. In this chapter, an effective method is proposed to identify the traffic signs in an automated manner. The traffic sign recognition for advanced driver-assistance system of Method I comprises of three stages: (1) detection using Haar-like features with AdaBoost method, (2) feature extraction using speeded up robust features, and (3) classification using support vector machine. Method II comprises of two stages: (1) detection of traffic sign using convolution neural network and (2) classification using convolution neural network. The performance of the system is analyzed. From the experimental results, it is observed that the Method II using convolution neural network gives a better performance compared with Method I