Fingerprint Matching Using Dual Hilbert Scans

A new fingerprint matching algorithm using dual Hilbert scans is presented in this study. We treat the fingerprint matching as point pattern matching problem and Hilbert scans are used in two aspects of the matching problem: one is applied to the similarity measure and the other is used in search space reduction. The similarity measure named Hilbert Scanning Distance (HSD) can be computed fast by converting the 2-D coordinates of 2-D images into 1-D space information using Hilbert scan. On the other hand, the 3-D search space can be converted to a 1-D search space sequence. The proposed method has been tested on FVC2002 database. The experimental results show that our method can implement fingerprint matching robustly and efficiently. The performance evaluation EER (Equal-Error Rate) generally used is very low by our algorithm.