Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor

Abstract

Abstract. This paper reviews a well-known fingerprint matching algorithm that uses an orientation-based minutia descriptor. It introduces a set of improvements to the algorithm that increase the accuracy and speed, using the same features. The most significant improvement is in the global minutiae matching step, reducing the number of local matching minutiae and using multiple minutiae pairs for fingerprint alignment. We conduct a series of experiments over the four databases of FVC2004, showing that the modified algorithm outperforms its predecessor and other algorithms proposed in the literature.

Introducing an Experimental Framework in C# for Fingerprint Recognition

“…The algorithms evaluated are: MCC [4,5,10] (SDK v1.4 available in http://biolab.csr.unibo.it/ mccsdk.html), M3gl [20], JY [15], TK [30], PN [24], QYW [25], MJY [21], MTK [22], MPN [19], and MQYW [21]. All the algorithms are evaluated with their default parameters except for algorithm M3gl, whose parameter c (i.e.…”

Fingerprint Recognition System Powered by Improved Hybrid Technique Based on Minutia Features

“…Minutiae are the points where the ridge continuity breaks and they are typically represented as (x,y,θ); where (x,y) represent the 2D point coordinates, and θ the ridge direction at that point. As a minutiae-based matcher should be invariant to translation and rotation [3], the process of minutiae pairing is ambiguous. Thus, most matchers of this category use minutia descriptors (local minutia structures) to rapidly create the minutia correspondences.…”