Hand-dorsa vein recognition based on partition Local Binary Pattern

A new hand-dorsa vein recognition method based on Partition Local Binary Pattern (PLBP) is presented in this paper. The proposed method employs hand-dorsa vein images acquired from a low-cost, near infrared device. After preprocessing, the image is divided into sub-images. LBP uniform pattern features are extracted from all the sub-images, which are combined to form the feature vector for token vein texture features. The method is assessed using a similarity measure obtained by calculating the distance between the feature vectors of the tested sample and the target sample. The algorithm is tested on a database of 2040 images from 102 individuals built up by a custom-made acquisition device. The experimental results show that PLBP performs better than other features.