A multi-matcher system based on Knuckle-based features

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 (near zero Equal Error Rate).