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학술지 Multimodal Biometric Method that Combines Veins, Prints, and Shape of a Finger
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강병준, 박강령, 유장희, 김정녀
Optical Engineering, v.50 no.1, pp.1-13
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).
finger recognition, fuzzy score normalization, multimodal biometrics
KSP 제안 키워드
Biometric features, Fingerprint recognition, Fourier Descriptor, Multimodal Biometrics, Normalization method, Optical instrumentation, Principal Component analysis, Recognition Accuracy, Recognition method, Short time, Sum rule