A novel matching strategy for finger vein recognition

Abstract

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. The vein vessel network is a very important vein pattern for finger vein recognition. Based on this pattern, in the matching stage, the matched pixel ratio (MPR), Hamming distance (HD) and the mismatched ratio are commonly used as the matching algorithms to evaluate the similarity between two finger vein images. But these matching algorithms are calculated pixel by pixel, they are sensitive to the image translation and rotation. In this paper, a novel matching strategy region-based axis projection (RAP) is proposed for finger vein recognition. We first divide the vein pattern into small regions, then concatenate the projection of the vein distribution curves on the x-axis and y-axis of each region, and finally evaluate the similarity by calculating the projections of the whole vein pattern. Experimental results show that the proposed method can avoid image translation and rotation to some extent and achieve a better performance. © Springer-Verlag 2013.