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Neural Computing and Applications
Published in: Neural Computing and Applications 1/2009

01-01-2009 | Original Article

A multi-matcher system based on knuckle-based features

Authors: Loris Nanni, Alessandra Lumini

Published in: Neural Computing and Applications | Issue 1/2009

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Abstract

We describe a new multi-matcher biometric approach, using knuckle-based features extracted from the middle finger and from the ring finger, with fusion applied at the matching-score level. The features extraction is performed by Radon transform and by Haar wavelet, then these features are transformed by non-linear Fisher transform. Finally, the matching process is based on Parzen window classifiers. Moreover, we study a method based on tokenised pseudo-random numbers and user specific knuckle features. The experimental results show the effectiveness of the system in terms of equal error rate (EER) (near zero equal error rate).
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Footnotes
1
Implemented as in the function adapthisteq.m of matlab 7.0 image processing toolbox.
 
3
window width parameter = 1.
 
4
Implemented as in the function adapthisteq.m and imadjust.m of matlab 7.0 image processing toolbox.
 
Literature
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Connie T, Jin ATB, Ong MGK, Ling DNC (2005) An automated palmprint recognition system. Image Vis Comput 23:501–515CrossRef
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Daubechies I (1992) Ten lectures on wavelets. Capital City Press, VermontMATH
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Duda RO, Hart PE, Stork DG (2000) Pattern classification. 2nd edn Wiley, New York
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Jin ATB, Ling DNC, Goh A (2004) Biohashing: two factor authentication featuring fingerprint data and tokenised random number. Pattern Recognit 37(11):2245–2255CrossRef
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Li Q, Qiu Z, Sun D, Wu J (2004) Personal identification using knuckleprint, vol 2004. SINOBIOMETRICS, Guangzhou, pp 680–689, 13–14 December 2004
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Loog M, Duin RPW, Haeb-Umbach R (2001) Multiclass linear dimension reduction by weighted pairwise fisher criteria. IEEE Trans Pattern Anal Mach Intell 23:762–766CrossRef
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Maio D, Nanni L (2005) MultiHashing, human authentication featuring biometrics data and tokenised random number: a case study FVC2004. Neurocomputing 69:242–249CrossRef
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Nanni L, Lumini A (2007) An improved BioHashing for human authentication. Pattern Recognit 40(3):1057–1065MATHCrossRef
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Ribaric S, Fratric I (2005) A biometric identification system based on eigenpalm and eigenfinger features. IEEE Trans Pattern Anal Mach Intell 27(11):1698–1709CrossRef
Metadata
Title
A multi-matcher system based on knuckle-based features
Authors
Loris Nanni
Alessandra Lumini
Publication date
01-01-2009
Publisher
Springer-Verlag
Published in
Neural Computing and Applications / Issue 1/2009
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-007-0160-4

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