A Novel Approach For Finger Vein Verification Based on Self-Taught Learning

2015/08/15 by Fayyaz, Mohsen, PourReza, Masoud, Saffar, Mohammad Hajizadeh +2
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.1508.03710

Abstract

In this paper, we propose a method for user Finger Vein Authentication (FVA) as a biometric system. Using the discriminative features for classifying theses finger veins is one of the main tips that make difference in related works, Thus we propose to learn a set of representative features, based on autoencoders. We model the user finger vein using a Gaussian distribution. Experimental results show that our algorithm perform like a state-of-the-art on SDUMLA-HMT benchmark.

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