Neural Computing and Applications

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

A multi-matcher system based on knuckle-based features

Original Article


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).


Biometrics Knuckle-print verification Radon transform Haar wavelet 



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 ( 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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