Abstract:
The use of human finger-vein traits for the purpose of automatic user recognition has
gained a lot of attention in recent years. Current state-of-the-art techniques can provide
relatively good performance, yet they are strongly dependent upon the quality of the analysed
finger-vein images. In this paper, I propose a convolutional-neural-network-based finger-
vein identification system and investigate the capabilities of the designed network over four
publicly available databases. The main purpose of this paper is to propose a deep-learning
method for finger-vein identification, which is able to achieve stable and highly accurate
performance when dealing with finger-vein images of different quality. The reported extensive
set of experiments show that the accuracy achievable with the proposed approach can go
beyond 95 percent correct identification rate for all the four considered publicly available
databases.
Index Terms :- Convolutional neural network, finger-vein, biometrics, identification.
