A Vision System for Traffic Sign Detection and Recognition

The paper presents an automatic traffic sign recognition system using the videos recorded from an on-board dashcam. It is based on image processing, bilateral Chinese transform, and vertex and bisector transform techniques. The images captured from the dashcam are processed with the histogram of oriented gradients to form feature vectors, followed by support vector machines to detect the traffic signs. The bilateral Chinese transform and vertex and bisector transform are used to extract the area of traffic sign from images. Finally, a neural network is adopted to identify the traffic sign information. In this work, we test the algorithms using the images captured from the camera mounted behind the front windshield. The experiments are evaluated with real traffic scenes and the results have demonstrated the effectiveness of the proposed system.