A finger-vein verification system using mean curvature

Authors:
Wonseok Song;Taejeong Kim;Hee Chan Kim;Joon Hwan Choi;Hyoun-Joong Kong;Seung-Rae Lee
Affiliations:
School of Electrical Engineering and the Institute of New Media and Communications, Seoul National University, South Korea;School of Electrical Engineering and the Institute of New Media and Communications, Seoul National University, South Korea;Department of Biomedical Engineering, College of Medicine and Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, South Korea;School of Electrical Engineering and the Institute of New Media and Communications, Seoul National University, South Korea;Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, South Korea;The Institute of New Media and Communications and jFinger Co., Ltd., Seoul National University, Daehak-dong, Gwanak-gu, Seoul, South Korea
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

The finger-vein pattern is one of the human biometric signatures that can be used for personal verification. The first task of a verification process using finger-vein patterns is extracting the pattern from an infrared finger image. As a robust extraction method, we propose the mean curvature method, which views the vein image as a geometric shape and finds the valley-like structures with negative mean curvatures. When the matched pixel ratio is used in matching vein patterns, experimental results show that, while maintaining low complexity, the proposed method achieves 0.25% equal error rate, which is significantly lower than what existing methods can achieve.