Palmprint Recognition Systems (PRS) with multi-feature can increase the recognition performance of PRS. For such a purpose, effectively distinguished information with low dimension is important in fusion for palmprint recognition. Usually, color information is a beneficial feature in image retrieval. But it is always ignored in recognition. This paper proposes a novel palmprint recognition algorithm based on multi-color components fusion. Firstly, an improved DCT-based approach is used to extract color component features from RGB space, YIQ space and HSI space, respectively. Secondly, the extracted useful component features are fused to serial-fused feature vectors. Then, classification is performed by the nearest neighbor classifier. Experimental results show that the proposed fusion algorithm obtains higher recognition rates compared to single component feature.
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