A Method of Fast and Robust for Traffic Sign Recognition

This paper proposes a fast and robust algorithm for traffic sign detection and recognition. The algorithm includes two stages: traffic sign detection and recognition. In the first stage, Adaboost algorithm based red pixels model of speed limit sign in the Lab color space is built. Then the model is used to extract area of latent speed limit signs. After that, the improved Hough Transform is used to locate the signs precisely. In the second stage, the template matching algorithm is used to recognize the traffic sign. At the same time, a new method of rejecting non-signs is presented, which improved the recognition rate in the complex outdoor scenes.