In order to assist driver's vision, a real-time recognition system for traffic signs is proposed. After detecting sign candidates, biologically inspired opponent-color filters are used to extract symbol parts of signs. After normalizing the size of symbol, structural features are calculated to identify the sign. 5572 segmented images are used to design the algorithm. In a real-time system, the same sign in a sequence of frames is tracked, and a majority vote is used to integrate the recognition results. For test data, 93.8% recall rate and 99.3% precision rate could be attained. In-vehicle experiment also showed high recall and precision rates.
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