Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning

Ekta Gavas, Kaustubh Olpadkar, Anoop Namboodiri

2024

Abstract

Fingerprint recognition stands as a pivotal component of biometric technology, with diverse applications from identity verification to advanced search tools. In this paper, we propose a unique method for deriving robust fingerprint representations by leveraging enhancement-based pre-training. Building on the achievements of U-Net-based fingerprint enhancement, our method employs a specialized encoder to derive representations from fingerprint images in a self-supervised manner. We further refine these representations, aiming to enhance the verification capabilities. Our experimental results, tested on publicly available fingerprint datasets, reveal a marked improvement in verification performance against established self-supervised training techniques. Our findings not only highlight the effectiveness of our method but also pave the way for potential advancements. Crucially, our research indicates that it is feasible to extract meaningful fingerprint representations from degraded images without relying on enhanced samples.

Paper Citation

in Harvard Style

Gavas E., Olpadkar K. and Namboodiri A. (2024). Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 821-828. DOI: 10.5220/0012474900003660

in Bibtex Style

@conference{visapp24,
author={Ekta Gavas and Kaustubh Olpadkar and Anoop Namboodiri},
title={Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2024},
pages={821-828},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012474900003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Enhancement-Driven Pretraining for Robust Fingerprint Representation Learning
SN - 978-989-758-679-8
AU - Gavas E.
AU - Olpadkar K.
AU - Namboodiri A.
PY - 2024
SP - 821
EP - 828
DO - 10.5220/0012474900003660
PB - SciTePress