A multi-matcher system based on knuckle-based features
- 183 Downloads
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).
KeywordsBiometrics 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 (http://126.96.36.199/prtools/). The authors would like to thank Federico D’Almeida for sharing the diffusion filtering toolbox.