Traffic Sign Recognition Based on Parameter-free Detector and DT-CWT

For the traffic sign which is difficult to detect in traffic environment, a traffic sign detection and recognition algorithm is proposed. First, the main colors of the traffic sign are segmented, the region of interest is expanded and its edge is extract. Then the edge is roughly divided by drawing linear and removing miscellaneous points. Turing angle curvature is computed according to the relations among the curvatures of the vertices. Then the vertex type is classified. The standard shapes such as circular, triangle, rectangle, are detected by parameter-free detector. The candidate regions are sent into the shape classifier to classify the type and exclude the interference. Finally, the type of traffic sign is recognized by dual tree complex wavelet transform and two-dimensional independent component analysis. The experimental results show that the detection and recognition rate of the proposed algorithm is high for the conditions such as traffic signs obscured, uneven illumination, color distortion, and it can achieve the effect of real-time processing.