On the importance of using high resolution images, third level features and sequence of images for fingerprint spoof detection
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
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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Repositório Institucional da UNESP |
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2946 |
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 |
|
_version_ |
1808128837484019712 |