Palm vein identification based on partial least square

Abstract

Palm vein identification is a novel biometric technology. Palm vein has high security and very convenient for the user. Many users like this kind of biometric which only use their hands. However, for the NIR light scattering in the skin and difference from different time capture, the recognition performance is not perfect. This paper proposes the algorithm based on partial least squares to extract some directions to compose the classify subspace. The direction change obviously in gray level and has the maximum relationship with the classical information. The coordinate of image in this subspace is used to classification and recognition. Classification is according to the image position in this space. Automation research institute of Chinese academy of sciences database was used to experimental analysis. When the component number is 240, the recognition performance of this scheme reaches the best value: CRR: 98.70%, FAR: 1.30%, FRR: 1.33%. The recognition time is 0.8196s at this component number. Experimental results show that this algorithm improves the recognition performance, suitable for security, attendance, etc, have practical value.