White-Box Evaluation of Fingerprint Matchers: Robustness to Minutiae Perturbations

TL;DR

This paper conducts a detailed white-box evaluation of fingerprint matchers, revealing their vulnerabilities to non-linear distortions and missing minutiae, which are critical for improving system robustness.

Contribution

It provides the first controlled white-box assessment of minutiae-based fingerprint matchers' robustness to various perturbations.

Findings

Match performance degrades more with non-linear distortions.

Missing minutiae significantly impact matching accuracy.

Spurious minutiae and small displacements have less effect.

Abstract

Prevailing evaluations of fingerprint recognition systems have been performed as end-to-end black-box tests of fingerprint identification or authentication accuracy. However, performance of the end-to-end system is subject to errors arising in any of its constituent modules, including: fingerprint scanning, preprocessing, feature extraction, and matching. Conversely, white-box evaluations provide a more granular evaluation by studying the individual sub-components of a system. While a few studies have conducted stand-alone evaluations of the fingerprint reader and feature extraction modules of fingerprint recognition systems, little work has been devoted towards white-box evaluations of the fingerprint matching module. We report results of a controlled, white-box evaluation of one open-source and two commercial-off-the-shelf (COTS) minutiae-based matchers in terms of their robustness against controlled perturbations (random noise and non-linear distortions) introduced into the input minutiae feature sets. Our white-box evaluations reveal that the performance of fingerprint minutiae matchers are more susceptible to non-linear distortion and missing minutiae than spurious minutiae and small positional displacements of the minutiae locations.