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Research of dual-modal decision level fusion for fingerprint and finger vein image

Research of dual-modal decision level fusion for fingerprint and finger vein image The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers' recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system. Keywords: biometrics; concatenated classifier; finger vein verification; decision level fusion; fingerprint; minutiae feature. Reference to this paper should be made as follows: Ma, H., Popoola, O.P. and Sun, S. (2015) ` for fingerprint and finger vein image', Int. J. Biometrics, Vol. 7, No. 3, pp.271­285. Biographical notes: Hui Ma received her PhD from Harbin Engineering University in 2011. Currently, she is a Lecturer at the College of Electronic Engineering, Heilongjiang University, China. Her research interests include pattern recognition and intelligent monitoring, finger vein and http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Research of dual-modal decision level fusion for fingerprint and finger vein image

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Publisher
Inderscience Publishers
Copyright
Copyright © 2015 Inderscience Enterprises Ltd.
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2015.071949
Publisher site
See Article on Publisher Site

Abstract

The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers' recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system. Keywords: biometrics; concatenated classifier; finger vein verification; decision level fusion; fingerprint; minutiae feature. Reference to this paper should be made as follows: Ma, H., Popoola, O.P. and Sun, S. (2015) ` for fingerprint and finger vein image', Int. J. Biometrics, Vol. 7, No. 3, pp.271­285. Biographical notes: Hui Ma received her PhD from Harbin Engineering University in 2011. Currently, she is a Lecturer at the College of Electronic Engineering, Heilongjiang University, China. Her research interests include pattern recognition and intelligent monitoring, finger vein and

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2015

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