A large-scale operational study of fingerprint quality and demographics
<|reference_start|>A large-scale operational study of fingerprint quality and demographics: 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.<|reference_end|>
@article{galbally2024a,
    title={A large-scale operational study of fingerprint quality and demographics},
    author={Javier Galbally, Aleksandrs Cepilovs, Ramon Blanco-Gonzalo, Gillian
  Ormiston, Oscar Miguel-Hurtado, and Istvan Sz. Racz},
    journal={arXiv preprint arXiv:2409.19992},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.19992},
    primaryClass={cs.CV cs.AI cs.LG}
}