Fast Recognition Algorithm For Static Traffic Sign Information

Aiming at the low recognition rate, low recognition efficiency, poor anti-interference and high missing detection rate of current traffic sign recognition methods, a fast recognition algorithm based on SURF for static traffic sign information of highway is proposed. The expansion of the digital morphological method is used to connect the cracks in the traffic sign. Traffic sign images are corroded according to the corrosion, and the connected areas are contracted or refined. Regions of interest are detected by region filling. According to the result of traffic sign image processing, the scale of traffic sign image is normalized by bilinear interpolation method, and the SURF feature points of traffic sign image are extracted. The FLANN algorithm is used to realize feature point matching, and the threshold is set to determine the best matching point. The matching result is output and the traffic sign information is recognized. Experimental results show that the algorithm has high recognition rate and recognition efficiency, strong anti-interference, and can control the rate of missing detection in a certain range.