An Efficient Contact Lens Spoofing Classification

Guilherme Silva, Pedro Silva, Mariana Mota, Eduardo Luz, Gladston Moreira

2022

Abstract

Spoofing detection, when differentiating illegitimate users from genuine ones, is a major problem for biometric systems and these techniques could be an enhancement in the industry. Nowadays iris recognition systems are very popular, once it is more precise for person authentication when compared to fingerprints and other biometric modalities. Nevertheless, iris recognition systems are vulnerable to spoofing via textured cosmetic contact lenses and techniques to avoid those attacks are imperative for a well system behavior and could be embedded. In this work, attention is centered on a three-class iris spoofing detection problem: textured/colored contact lenses, soft contact lenses, and no lenses. Our approach adapts the Inverted Bottleneck Convolution blocks from the EfficientNets to build deep image representation. Experiments are conducted in comparison with the literature on two public iris image databases for contact lens detection: Notre Dame and IIIT-Delhi. With transfer learning, we surpass previous approaches in most of the cases for both databases with very promising results.

Paper Citation

in Harvard Style

Silva G., Silva P., Mota M., Luz E. and Moreira G. (2022). An Efficient Contact Lens Spoofing Classification. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 441-448. DOI: 10.5220/0010868500003179

in Bibtex Style

@conference{iceis22,
author={Guilherme Silva and Pedro Silva and Mariana Mota and Eduardo Luz and Gladston Moreira},
title={An Efficient Contact Lens Spoofing Classification},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={441-448},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010868500003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - An Efficient Contact Lens Spoofing Classification
SN - 978-989-758-569-2
AU - Silva G.
AU - Silva P.
AU - Mota M.
AU - Luz E.
AU - Moreira G.
PY - 2022
SP - 441
EP - 448
DO - 10.5220/0010868500003179