A large-scale operational study of fingerprint quality and demographics

TL;DR

This large-scale study investigates how demographic factors like gender, age, and finger type influence fingerprint quality and recognition accuracy, revealing performance disparities across different population segments.

Contribution

It provides comprehensive data-driven insights into demographic impacts on fingerprint quality, highlighting variability and proposing follow-up actions to improve fairness in biometric systems.

Findings

Performance variability across demographic groups

Correlation between fingerprint quality and recognition accuracy

Potential strategies to reduce demographic biases

Abstract

Even though a few initial works have shown on small sets of data some level of bias in the performance of fingerprint recognition technology with respect to certain demographic groups, there is still not sufficient evidence to understand the impact that certain factors such as gender, age or finger-type may have on fingerprint quality and, in turn, also on fingerprint matching accuracy. The present work addresses this still under researched topic, on a large-scale database of operational data containing 10-print impressions of almost 16,000 subjects. The results reached provide further insight into the dependency of fingerprint quality and demographics, and show that there in fact exists a certain degree of performance variability in fingerprint-based recognition systems for different segments of the population. Based on the experimental evaluation, the work points out new observations based on data-driven evidence, provides plausible hypotheses to explain such observations, and concludes with potential follow-up actions that can help to reduce the observed fingerprint quality differences. This way, the current paper can be considered as a contribution to further increase the algorithmic fairness and equality of biometric technology.