Detection and recognition of speed limit sign from video

Abstract

The proper identification of speed limit traffic sighs can alarm the drivers the highest speed allowed and can effictively reduce the number of traffic accidents. In this paper, we put forward an efficient detection method for speed limit traffic signs based on the fast radial symmetry transform with new Sobel operator. when we detected the speed limit traffic sign, we need to segment the digits. Digit segmentation is achieved by cropping the candidate traffic sign from the traffic scene, making use of Otsu thresholding algorithm to binary it, and normalizing it to a uniform size. Finally we recognize and classify the signs using DAG-SVMs classifier which is trained for this purpose. In cloudy weather conditions and dusk illumination condition, we tested 10 videos about 28min. The recognition rate of frames which contain speed limit sign is 90.48%.