Palm Vein Verification Using Multiple Features and Isometric Projection

Abstract

Biometric authentication has been widely studied for many years and attracted much attention due to its large ability security application. Palm vein is more immovable and more difficult to fake than other biometrics such as fingerprint, palm print and face. Since palm veins exist inside of the body, it is exceedingly hard to be forged. Palm vein authentication uses the unique patterns of the palm vein to identify individuals at a high level of accuracy. In the proposed work, the palm vein image enhancement algorithm proposed based on Gaussian matched filtering and then two types of feature extraction are extracted. The global features based on wavelet coefficients and locale feature based on local binary pattern (LBP). In the propose work, a linear dimensionality reduction algorithm, called Isometric Projection is used. Finally, the Manhattan Distance (MHD) matching method is proposed to verify the test palm vein images. The experimental result shows the EER to the proposed method is 0.17488%.