A novel fingerprint matching method using a curvature-based minutia specifier

A new fingerprint matching algorithm using the elaborate combination of minutiae and curvature maps from fingerprint images is proposed in this paper. First of all, we propose a simple method for curvature calculation based on fingerprint orientation fields from fingerprint images. Secondly, a curvature-based minutia specifier, which appears to be a circular pattern, is introduced by taking sampling steps on curvature map around a minutia serving as a sampling center. Thirdly, a measurement on similarity degree between two minutia specifiers is presented and a reference corresponding minutia pair validation algorithm is also described based on the reliable and maximum curvature points to increase the accuracy of our system. Finally, a fingerprint matching algorithm, based on our proposed minutia specifiers, is developed and tested on a public domain collection of fingerprint images, DB1 set A, FVC2002. The results demonstrate the good performance of our method proposed here.