On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection

Detalhes bibliográficos
Autor(a) principal: Da Silva, Murilo Varges [UNESP]
Data de Publicação: 2015
Outros Autores: Marana, Aparecido Nilceu [UNESP], Paulino, Alessandra Aparecida [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ICASSP.2015.7178282
http://hdl.handle.net/11449/177574
Resumo: The successful and widespread deployment of biometric systems brings on a new challenge: the spoofing, which involves presenting an artificial or fake biometric trait to the biometric systems so that unauthorized users can gain access to places and/or information. We propose a fingerprint spoof detection method that uses a combination of information available from pores, statistical features and fingerprint image quality to classify the fingerprint images into live or fake. Our spoof detection algorithm combines these three types of features to obtain an average accuracy of 97.3% on a new database (UNESP-FSDB) that contains 4,800 images of live and fake fingerprints. An analysis is performed that considers some issues such as image resolution, pressure by the user, sequence of images and level of features.
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spelling On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detectionBiometricsfingerprintporessecurityspoof detectionThe successful and widespread deployment of biometric systems brings on a new challenge: the spoofing, which involves presenting an artificial or fake biometric trait to the biometric systems so that unauthorized users can gain access to places and/or information. We propose a fingerprint spoof detection method that uses a combination of information available from pores, statistical features and fingerprint image quality to classify the fingerprint images into live or fake. Our spoof detection algorithm combines these three types of features to obtain an average accuracy of 97.3% on a new database (UNESP-FSDB) that contains 4,800 images of live and fake fingerprints. An analysis is performed that considers some issues such as image resolution, pressure by the user, sequence of images and level of features.Department of Computing, Faculty of Sciences, Sao Paulo State University (UNESP)Department of Computing, Faculty of Sciences, Sao Paulo State University (UNESP)Universidade Estadual Paulista (Unesp)Da Silva, Murilo Varges [UNESP]Marana, Aparecido Nilceu [UNESP]Paulino, Alessandra Aparecida [UNESP]2018-12-11T17:26:01Z2018-12-11T17:26:01Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1807-1811application/pdfhttp://dx.doi.org/10.1109/ICASSP.2015.7178282ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v. 2015-August, p. 1807-1811.1520-6149http://hdl.handle.net/11449/17757410.1109/ICASSP.2015.71782822-s2.0-849460646162-s2.0-84946064616.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedingsinfo:eu-repo/semantics/openAccess2024-04-23T16:11:20Zoai:repositorio.unesp.br:11449/177574Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:38:19.075581Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
title On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
spellingShingle On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
Da Silva, Murilo Varges [UNESP]
Biometrics
fingerprint
pores
security
spoof detection
title_short On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
title_full On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
title_fullStr On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
title_full_unstemmed On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
title_sort On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
author Da Silva, Murilo Varges [UNESP]
author_facet Da Silva, Murilo Varges [UNESP]
Marana, Aparecido Nilceu [UNESP]
Paulino, Alessandra Aparecida [UNESP]
author_role author
author2 Marana, Aparecido Nilceu [UNESP]
Paulino, Alessandra Aparecida [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Da Silva, Murilo Varges [UNESP]
Marana, Aparecido Nilceu [UNESP]
Paulino, Alessandra Aparecida [UNESP]
dc.subject.por.fl_str_mv Biometrics
fingerprint
pores
security
spoof detection
topic Biometrics
fingerprint
pores
security
spoof detection
description The successful and widespread deployment of biometric systems brings on a new challenge: the spoofing, which involves presenting an artificial or fake biometric trait to the biometric systems so that unauthorized users can gain access to places and/or information. We propose a fingerprint spoof detection method that uses a combination of information available from pores, statistical features and fingerprint image quality to classify the fingerprint images into live or fake. Our spoof detection algorithm combines these three types of features to obtain an average accuracy of 97.3% on a new database (UNESP-FSDB) that contains 4,800 images of live and fake fingerprints. An analysis is performed that considers some issues such as image resolution, pressure by the user, sequence of images and level of features.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01
2018-12-11T17:26:01Z
2018-12-11T17:26:01Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ICASSP.2015.7178282
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v. 2015-August, p. 1807-1811.
1520-6149
http://hdl.handle.net/11449/177574
10.1109/ICASSP.2015.7178282
2-s2.0-84946064616
2-s2.0-84946064616.pdf
url http://dx.doi.org/10.1109/ICASSP.2015.7178282
http://hdl.handle.net/11449/177574
identifier_str_mv ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v. 2015-August, p. 1807-1811.
1520-6149
10.1109/ICASSP.2015.7178282
2-s2.0-84946064616
2-s2.0-84946064616.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1807-1811
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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