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Enhanced fingerprint authentication: a deep learning and error correction-based biometric cryptosystem

Published Online: 2025-10-21

Published Print: 2026-03

Authors

Mathew, Netha Merin https://orcid.org/0009-0006-7995-0528
Muthukumar, A.
License Information

Text and Data Mining valid from 2025-10-21

Version of Record valid from 2025-10-21
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Article History

Received: 4 February 2025

Accepted: 27 September 2025

First Online: 21 October 2025

Declarations

:

: The authors have no financial or proprietary interests in any material discussed in this article.

: This research does not involve any human participants and/or animals. Human fingerprints are obtained from sokoto coventry fingerprint dataset which is available online.

: Here the work entitled”Enhanced Fingerprint Authentication: A Deep Learning and Error-correction based biometric cryptosystem” approach to fingerprint identification is mostly based on feature extraction techniques mixed with error correction approaches to improve accuracy and reliability. This study presents a novel biometric cryptosystem that combines deep learning (DL) with Reed-Solomon (RS) error-correcting codes to increase the reliability of fingerprint-based identification, utilizing the Sokoto Coventry Fingerprint (SOCOFing) dataset.There is no risk involved in this work.

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