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Finger vein recognition based on finger crease location

[+] Author Affiliations
Zhiying Lu, Shumeng Ding, Jing Yin

Tianjin University, School of Electrical Engineering and Automation, Automation, 92 Weijin Road, Nankai District, Tianjin 300072, China

J. Electron. Imaging. 25(4), 043004 (Jul 11, 2016). doi:10.1117/1.JEI.25.4.043004
History: Received March 2, 2016; Accepted June 23, 2016
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Abstract.  Finger vein recognition technology has significant advantages over other methods in terms of accuracy, uniqueness, and stability, and it has wide promising applications in the field of biometric recognition. We propose using finger creases to locate and extract an object region. Then we use linear fitting to overcome the problem of finger rotation in the plane. The method of modular adaptive histogram equalization (MAHE) is presented to enhance image contrast and reduce computational cost. To extract the finger vein features, we use a fusion method, which can obtain clear and distinguishable vein patterns under different conditions. We used the Hausdorff average distance algorithm to examine the recognition performance of the system. The experimental results demonstrate that MAHE can better balance the recognition accuracy and the expenditure of time compared with three other methods. Our resulting equal error rate throughout the total procedure was 3.268% in a database of 153 finger vein images.

© 2016 SPIE and IS&T

Citation

Zhiying Lu ; Shumeng Ding and Jing Yin
"Finger vein recognition based on finger crease location", J. Electron. Imaging. 25(4), 043004 (Jul 11, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.4.043004


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