Neural Computing and Applications

, Volume 18, Issue 1, pp 87–91 | Cite as

A multi-matcher system based on knuckle-based features

Original Article

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).

Keywords

Biometrics Knuckle-print verification Radon transform Haar wavelet 

Notes

Acknowledgment

This work has been supported by European Commission IST-2002-507634 Biosecure NoE projects. Several methods (PCA, P, N, F and NL) have been implemented as in PRTools 3.1.7 (http://130.161.42.18/prtools/). The authors would like to thank Federico D’Almeida for sharing the diffusion filtering toolbox.

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Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  1. 1.DEIS, IEIIT-CNRUniversità di BolognaBolognaItaly

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