Finger Vein Recognition by Combining Global and Local Features based on SVM

Authors

  • Kang Ryoung Park

Keywords:

Biometrics, finger vein recognition, LBP, Wavelet transform, SVM

Abstract

Recently, biometrics such as fingerprints, faces and irises recognition have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins to identify individuals at a high level of accuracy. This paper proposes new algorithms for finger vein recognition. This research presents the following three advantages and contributions compared to previous works. First, we extracted local information of the finger veins based on a LBP (Local Binary Pattern) without segmenting accurate finger vein regions. Second, the global information of the finger veins based on Wavelet transform was extracted. Third, two score values by the LBP and Wavelet transform were combined by the SVM (Support Vector Machine). As experimental results, the EER (Equal Error Rate) was 0.011 % and the total processing time was 98.2ms.

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Author Biography

Kang Ryoung Park

Division of Electronics and Electrical Engineering
Dongguk University
26, Pildong-3 ga, Jung-gu, Seoul
Republic of Korea

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Published

2012-01-26

How to Cite

Park, K. R. (2012). Finger Vein Recognition by Combining Global and Local Features based on SVM. COMPUTING AND INFORMATICS, 30(2), 295–309. Retrieved from https://www.cai.sk/ojs/index.php/cai/article/view/172