Finger vein recognition based on finger crease location

Zhiying Lu; Shumeng Ding; Jing Yin

doi:10.1117/1.JEI.25.4.043004

11 July 2016 Finger vein recognition based on finger crease location

Zhiying Lu, Shumeng Ding, Jing Yin

Author Affiliations +

Journal of Electronic Imaging, Vol. 25, Issue 4, 043004 (July 2016). https://doi.org/10.1117/1.JEI.25.4.043004

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.

Citation Download Citation

Zhiying Lu, Shumeng Ding, and Jing Yin "Finger vein recognition based on finger crease location," Journal of Electronic Imaging 25(4), 043004 (11 July 2016). https://doi.org/10.1117/1.JEI.25.4.043004

Published: 11 July 2016

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