A new method for the detection of singular points in fingerprint images
Autor(a) principal: | |
---|---|
Data de Publicação: | 2009 |
Outros Autores: | , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/19474 |
Resumo: | Automatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincaré Indexbased methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%. |
id |
RCAP_47323222b9ed9f04f14b8ef57a332d9f |
---|---|
oai_identifier_str |
oai:repositorio-aberto.up.pt:10216/19474 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
A new method for the detection of singular points in fingerprint imagesProcessamento de imagem, Engenharia electrotécnica, electrónica e informáticaImage processing, Electrical engineering, Electronic engineering, Information engineeringAutomatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincaré Indexbased methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%.20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/19474eng10.1109/WACV.2009.5403106Filipe Tiago Alves de MagalhãesHélder P. de OliveiraAurélio C. Campilhoinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:04:57Zoai:repositorio-aberto.up.pt:10216/19474Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:54:18.244557Repositório 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 |
A new method for the detection of singular points in fingerprint images |
title |
A new method for the detection of singular points in fingerprint images |
spellingShingle |
A new method for the detection of singular points in fingerprint images Filipe Tiago Alves de Magalhães Processamento de imagem, Engenharia electrotécnica, electrónica e informática Image processing, Electrical engineering, Electronic engineering, Information engineering |
title_short |
A new method for the detection of singular points in fingerprint images |
title_full |
A new method for the detection of singular points in fingerprint images |
title_fullStr |
A new method for the detection of singular points in fingerprint images |
title_full_unstemmed |
A new method for the detection of singular points in fingerprint images |
title_sort |
A new method for the detection of singular points in fingerprint images |
author |
Filipe Tiago Alves de Magalhães |
author_facet |
Filipe Tiago Alves de Magalhães Hélder P. de Oliveira Aurélio C. Campilho |
author_role |
author |
author2 |
Hélder P. de Oliveira Aurélio C. Campilho |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Filipe Tiago Alves de Magalhães Hélder P. de Oliveira Aurélio C. Campilho |
dc.subject.por.fl_str_mv |
Processamento de imagem, Engenharia electrotécnica, electrónica e informática Image processing, Electrical engineering, Electronic engineering, Information engineering |
topic |
Processamento de imagem, Engenharia electrotécnica, electrónica e informática Image processing, Electrical engineering, Electronic engineering, Information engineering |
description |
Automatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincaré Indexbased methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009 2009-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/19474 |
url |
https://hdl.handle.net/10216/19474 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1109/WACV.2009.5403106 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799135862850584577 |