Contactless Biometric Based on Palm Vein Recognition Using Wavelet and Local Line Binary Patterns

Abstract

Palm vein recognition has received much attention due to its advantages compared to other biometrics. Because it is contactless, this biometric system does not require physical contact between the user and the sensor device, thus providing several advantages in terms of comfort during acquisition and being more hygienic. In the palm vein recognition system, the palm vein pattern can be considered as a texture feature. Therefore, this study proposes a contactless biometric system based on palm vein recognition using the Local Line Binary Pattern method for extracting texture features of palm vein images resulting from the decomposition of 2D Wavelet Transformation, to produce a texture descriptor that is small and compatible with the texture characteristics of thin veins. The proposed texture feature extraction method has been tested using the Fuzzy k-NN classification method on 600 palm images with a CRR accuracy of 94.0% with a computation time of 0.057 seconds.