Abstract
Dorsal hand vein recognition based on wavelet decomposition and K2DPCA-2DLDA was proposed in this paper,and db4 wavelet was used to decompose the original image.K2DPCA transformation was used for the sub-image of low frequency to obtain low dimensional space characteristics.Then,2DLDA transformation was used to further reduce the dimension for obtaining the final feature expression.Finally,the features were classified according to the nearest neighbor classification rule.The experimental results show that the method can improve the hand dorsal vein recognition rate and reduce the recognition time effectively.
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