Robust iris localisation in challenging scenarios

Detalhes bibliográficos
Autor(a) principal: Monteiro,JC
Data de Publicação: 2014
Outros Autores: Sequeira,AF, Hélder Filipe Oliveira, Jaime Cardoso
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/3583
http://dx.doi.org/10.1007/978-3-662-44911-0_10
Resumo: The use of images acquired in unconstrained scenarios is giving rise to new challenges in the field of iris recognition. Many works in literature reported excellent results in both iris segmentation and recognition but mostly with images acquired in controlled conditions. The intention to broaden the field of application of iris recognition, such as airport security or personal identification in mobile devices, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focuses on mutual context information from iris centre and iris limbic and pupillary contours to perform robust and accurate iris segmentation in noisy images. The developed algorithm was tested on the MobBIO database with a promising 96% segmentation accuracy for the limbic contour.
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spelling Robust iris localisation in challenging scenariosThe use of images acquired in unconstrained scenarios is giving rise to new challenges in the field of iris recognition. Many works in literature reported excellent results in both iris segmentation and recognition but mostly with images acquired in controlled conditions. The intention to broaden the field of application of iris recognition, such as airport security or personal identification in mobile devices, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focuses on mutual context information from iris centre and iris limbic and pupillary contours to perform robust and accurate iris segmentation in noisy images. The developed algorithm was tested on the MobBIO database with a promising 96% segmentation accuracy for the limbic contour.2017-11-20T10:43:33Z2014-01-01T00:00:00Z2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/3583http://dx.doi.org/10.1007/978-3-662-44911-0_10engMonteiro,JCSequeira,AFHélder Filipe OliveiraJaime Cardosoinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:57Zoai:repositorio.inesctec.pt:123456789/3583Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:51.248629Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Robust iris localisation in challenging scenarios
title Robust iris localisation in challenging scenarios
spellingShingle Robust iris localisation in challenging scenarios
Monteiro,JC
title_short Robust iris localisation in challenging scenarios
title_full Robust iris localisation in challenging scenarios
title_fullStr Robust iris localisation in challenging scenarios
title_full_unstemmed Robust iris localisation in challenging scenarios
title_sort Robust iris localisation in challenging scenarios
author Monteiro,JC
author_facet Monteiro,JC
Sequeira,AF
Hélder Filipe Oliveira
Jaime Cardoso
author_role author
author2 Sequeira,AF
Hélder Filipe Oliveira
Jaime Cardoso
author2_role author
author
author
dc.contributor.author.fl_str_mv Monteiro,JC
Sequeira,AF
Hélder Filipe Oliveira
Jaime Cardoso
description The use of images acquired in unconstrained scenarios is giving rise to new challenges in the field of iris recognition. Many works in literature reported excellent results in both iris segmentation and recognition but mostly with images acquired in controlled conditions. The intention to broaden the field of application of iris recognition, such as airport security or personal identification in mobile devices, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focuses on mutual context information from iris centre and iris limbic and pupillary contours to perform robust and accurate iris segmentation in noisy images. The developed algorithm was tested on the MobBIO database with a promising 96% segmentation accuracy for the limbic contour.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01T00:00:00Z
2014
2017-11-20T10:43:33Z
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http://dx.doi.org/10.1007/978-3-662-44911-0_10
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http://dx.doi.org/10.1007/978-3-662-44911-0_10
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