A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis

In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic c...

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Detalles Bibliográficos
Autores principales: Hsieh, Sheng-Hsun, Li, Yung-Hui, Wang, Wei, Tien, Chung-Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876747/
https://www.ncbi.nlm.nih.gov/pubmed/29509692
http://dx.doi.org/10.3390/s18030795
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author Hsieh, Sheng-Hsun
Li, Yung-Hui
Wang, Wei
Tien, Chung-Hao
author_facet Hsieh, Sheng-Hsun
Li, Yung-Hui
Wang, Wei
Tien, Chung-Hao
author_sort Hsieh, Sheng-Hsun
collection PubMed
description In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme.
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spelling pubmed-58767472018-04-09 A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis Hsieh, Sheng-Hsun Li, Yung-Hui Wang, Wei Tien, Chung-Hao Sensors (Basel) Article In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme. MDPI 2018-03-06 /pmc/articles/PMC5876747/ /pubmed/29509692 http://dx.doi.org/10.3390/s18030795 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hsieh, Sheng-Hsun
Li, Yung-Hui
Wang, Wei
Tien, Chung-Hao
A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title_full A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title_fullStr A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title_full_unstemmed A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title_short A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis
title_sort novel anti-spoofing solution for iris recognition toward cosmetic contact lens attack using spectral ica analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876747/
https://www.ncbi.nlm.nih.gov/pubmed/29509692
http://dx.doi.org/10.3390/s18030795
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