Aiming at the problem that the accuracy rate of traffic sign detection will become significantly lower in protean illumination scenario ,a novel robust method of traffic sign detection is proposed based on the color probability map which is built from multiple color-histogram back-projection and the extraction of MSER (Maximally Stable Extremal Region) in color probability map .The algorithm consists of three steps :1) Sample images of traffic signs are classified into a series of different subsets with different illumination states for each color of interest (red ,blue or yellow ) and the color probability map is built from the multiple color-histogram built from each subset of sample images ;2) Candidate re-gions of traffic sign are found by using the extraction of MSER in color probability map ;3) Non-traffic-sign regions are e-liminated efficiently according to the features (region perimeter ,area ,etc .) of the detected MSER .Experimental results show that under the conditions of low light and strong light the accuracy rate of traffic sign detection algorithm based on normalized RGB drops to 84 .4% and 83 .0% respectively ,while the accuracy rate of traffic sign detection algorithm based on red/blue image drops to 87 .4% and 86 .3% respectively .The proposed method can still remain more than 90% of the detection accuracy in protean illumination scenario ,and is of higher robustness in protean illumination environment .
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