Minutiae Detection: An Image Exploring Agent-Based Model

Autores
Unanue, Ariel; Zapico, Adriana
Año de publicación
2002
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Identification through fingerprints is one of the most precise methods to determine a person’s identity. For years, this task has been carried out manually, but, due to the great number of fingerprints involved in the comparison, the implementation of an Automated Fingerprint Identification System (A.F.I.S.) emerged as a necessity. A critical process in automated fingerprint identification is minutiae extraction, process in which the presence of image noise or filth will generate undesired spikes and breaks that will lead to a considerable number of spurious minutiae. To overcome this problem, before minutiae detection, a usual process applied is a post-processing of the thinned image or pruning step, being the latter not always successful. In this paper, we introduce a new minutiae detection method, without the need of a pruning step, based on image exploring agents. First, reactive agents are used over the thinned fingerprint image, that detect locations of interest that could be minutiae using an efficient coefficient, which we propose, and to our knowledge, has not been applied before for minutiae detection. Then, several agents run through the image, starting at the locations of interest, to determine whether they are real minutiae or not. Having a more reliable method for minutiae detection would lead into a better performance of the whole recognition system.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
minutiae detection
image exploring agents
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/183076

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spelling Minutiae Detection: An Image Exploring Agent-Based ModelUnanue, ArielZapico, AdrianaCiencias Informáticasminutiae detectionimage exploring agentsIdentification through fingerprints is one of the most precise methods to determine a person’s identity. For years, this task has been carried out manually, but, due to the great number of fingerprints involved in the comparison, the implementation of an Automated Fingerprint Identification System (A.F.I.S.) emerged as a necessity. A critical process in automated fingerprint identification is minutiae extraction, process in which the presence of image noise or filth will generate undesired spikes and breaks that will lead to a considerable number of spurious minutiae. To overcome this problem, before minutiae detection, a usual process applied is a post-processing of the thinned image or pruning step, being the latter not always successful. In this paper, we introduce a new minutiae detection method, without the need of a pruning step, based on image exploring agents. First, reactive agents are used over the thinned fingerprint image, that detect locations of interest that could be minutiae using an efficient coefficient, which we propose, and to our knowledge, has not been applied before for minutiae detection. Then, several agents run through the image, starting at the locations of interest, to determine whether they are real minutiae or not. Having a more reliable method for minutiae detection would lead into a better performance of the whole recognition system.Sociedad Argentina de Informática e Investigación Operativa2002info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf37-49http://sedici.unlp.edu.ar/handle/10915/183076enginfo:eu-repo/semantics/altIdentifier/issn/1660-1079info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:50:02Zoai:sedici.unlp.edu.ar:10915/183076Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:50:03.03SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Minutiae Detection: An Image Exploring Agent-Based Model
title Minutiae Detection: An Image Exploring Agent-Based Model
spellingShingle Minutiae Detection: An Image Exploring Agent-Based Model
Unanue, Ariel
Ciencias Informáticas
minutiae detection
image exploring agents
title_short Minutiae Detection: An Image Exploring Agent-Based Model
title_full Minutiae Detection: An Image Exploring Agent-Based Model
title_fullStr Minutiae Detection: An Image Exploring Agent-Based Model
title_full_unstemmed Minutiae Detection: An Image Exploring Agent-Based Model
title_sort Minutiae Detection: An Image Exploring Agent-Based Model
dc.creator.none.fl_str_mv Unanue, Ariel
Zapico, Adriana
author Unanue, Ariel
author_facet Unanue, Ariel
Zapico, Adriana
author_role author
author2 Zapico, Adriana
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
minutiae detection
image exploring agents
topic Ciencias Informáticas
minutiae detection
image exploring agents
dc.description.none.fl_txt_mv Identification through fingerprints is one of the most precise methods to determine a person’s identity. For years, this task has been carried out manually, but, due to the great number of fingerprints involved in the comparison, the implementation of an Automated Fingerprint Identification System (A.F.I.S.) emerged as a necessity. A critical process in automated fingerprint identification is minutiae extraction, process in which the presence of image noise or filth will generate undesired spikes and breaks that will lead to a considerable number of spurious minutiae. To overcome this problem, before minutiae detection, a usual process applied is a post-processing of the thinned image or pruning step, being the latter not always successful. In this paper, we introduce a new minutiae detection method, without the need of a pruning step, based on image exploring agents. First, reactive agents are used over the thinned fingerprint image, that detect locations of interest that could be minutiae using an efficient coefficient, which we propose, and to our knowledge, has not been applied before for minutiae detection. Then, several agents run through the image, starting at the locations of interest, to determine whether they are real minutiae or not. Having a more reliable method for minutiae detection would lead into a better performance of the whole recognition system.
Sociedad Argentina de Informática e Investigación Operativa
description Identification through fingerprints is one of the most precise methods to determine a person’s identity. For years, this task has been carried out manually, but, due to the great number of fingerprints involved in the comparison, the implementation of an Automated Fingerprint Identification System (A.F.I.S.) emerged as a necessity. A critical process in automated fingerprint identification is minutiae extraction, process in which the presence of image noise or filth will generate undesired spikes and breaks that will lead to a considerable number of spurious minutiae. To overcome this problem, before minutiae detection, a usual process applied is a post-processing of the thinned image or pruning step, being the latter not always successful. In this paper, we introduce a new minutiae detection method, without the need of a pruning step, based on image exploring agents. First, reactive agents are used over the thinned fingerprint image, that detect locations of interest that could be minutiae using an efficient coefficient, which we propose, and to our knowledge, has not been applied before for minutiae detection. Then, several agents run through the image, starting at the locations of interest, to determine whether they are real minutiae or not. Having a more reliable method for minutiae detection would lead into a better performance of the whole recognition system.
publishDate 2002
dc.date.none.fl_str_mv 2002
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1660-1079
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
37-49
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repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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