Abstract：In order to improve the speed and accuracy of traffic signs recognition (TSR) , a novel method based on a visual attention model and scale invariant feature transform (SIFT) feature is proposed.First, color features are extracted based on the visual attention model, and the candidate regions of traffic signs could be achieved.Then, SIFT feature of the candidate region is extracted, and the similarity calculation is done between the candidate region and the standard traffic signs.Thus, the traffic sign would be recognized.The proposed method can recognize the traffic signs more rapidly and accurately than traditional methods, and it is characterized by no need for segmentation, less calculation, and bionics.The experiments results on two traffic signs databases collected from home and abroad show the excellent effect of the method on TSR.

Keyword：visual attention;SIFT;traffic signs;recognition;