1 January 2011 Multimodal biometric method that combines veins, prints, and shape of a finger
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Abstract
Multimodal biometrics provides high recognition accuracy and population coverage by using various biometric features. A single finger contains finger veins, fingerprints, and finger geometry features; by using multimodal biometrics, information on these multiple features can be simultaneously obtained in a short time and their fusion can outperform the use of a single feature. This paper proposes a new finger recognition method based on the score-level fusion of finger veins, fingerprints, and finger geometry features. This research is novel in the following four ways. First, the performances of the finger-vein and fingerprint recognition are improved by using a method based on a local derivative pattern. Second, the accuracy of the finger geometry recognition is greatly increased by combining a Fourier descriptor with principal component analysis. Third, a fuzzy score normalization method is introduced; its performance is better than the conventional Z-score normalization method. Fourth, finger-vein, fingerprint, and finger geometry recognitions are combined by using three support vector machines and a weighted SUM rule. Experimental results showed that the equal error rate of the proposed method was 0.254%, which was lower than those of the other methods.
© (2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Byung Jun Kang, Kang Ryoung Park, Jang-Hee Yoo, Jeong Nyeo Kim, "Multimodal biometric method that combines veins, prints, and shape of a finger," Optical Engineering 50(1), 017201 (1 January 2011). https://doi.org/10.1117/1.3530023 . Submission:
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