Automatic cattle identification using graph matching based on local invariant features

Bibliographic Details
Main Author: Monteiro, Fernando C.
Publication Date: 2016
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/16734
Summary: Cattle muzzle classification can be considered as a biometric identifier important to animal traceability systems to ensure the integrity of the food chain. This paper presents a muzzle-based classification system that combines local invariant features with graph matching. The proposed approach consists of three phases; namely feature extraction, graph matching, and matching refinement. The experimental results showed that our approach is superior than existing works as ours achieves an all correct identification for the tested images. In addition, the results proved that our proposed method achieved this high accuracy even if the testing images are rotated in various angles.
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network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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spelling Automatic cattle identification using graph matching based on local invariant featuresGraph matchingFeature extractionPattern recognitionCattle identificationCattle muzzle classification can be considered as a biometric identifier important to animal traceability systems to ensure the integrity of the food chain. This paper presents a muzzle-based classification system that combines local invariant features with graph matching. The proposed approach consists of three phases; namely feature extraction, graph matching, and matching refinement. The experimental results showed that our approach is superior than existing works as ours achieves an all correct identification for the tested images. In addition, the results proved that our proposed method achieved this high accuracy even if the testing images are rotated in various angles.Biblioteca Digital do IPBMonteiro, Fernando C.2018-04-06T13:25:52Z20162016-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10198/16734engMonteiro, Fernando C. (2016). Automatic cattle identification using graph matching based on local invariant features. In International Conference in Image Analysis and Recognition - ICIAR 2016. Póvoa de Varzim, Portugalinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T12:06:38Zoai:bibliotecadigital.ipb.pt:10198/16734Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:33:19.556444Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Automatic cattle identification using graph matching based on local invariant features
title Automatic cattle identification using graph matching based on local invariant features
spellingShingle Automatic cattle identification using graph matching based on local invariant features
Monteiro, Fernando C.
Graph matching
Feature extraction
Pattern recognition
Cattle identification
title_short Automatic cattle identification using graph matching based on local invariant features
title_full Automatic cattle identification using graph matching based on local invariant features
title_fullStr Automatic cattle identification using graph matching based on local invariant features
title_full_unstemmed Automatic cattle identification using graph matching based on local invariant features
title_sort Automatic cattle identification using graph matching based on local invariant features
author Monteiro, Fernando C.
author_facet Monteiro, Fernando C.
author_role author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Monteiro, Fernando C.
dc.subject.por.fl_str_mv Graph matching
Feature extraction
Pattern recognition
Cattle identification
topic Graph matching
Feature extraction
Pattern recognition
Cattle identification
description Cattle muzzle classification can be considered as a biometric identifier important to animal traceability systems to ensure the integrity of the food chain. This paper presents a muzzle-based classification system that combines local invariant features with graph matching. The proposed approach consists of three phases; namely feature extraction, graph matching, and matching refinement. The experimental results showed that our approach is superior than existing works as ours achieves an all correct identification for the tested images. In addition, the results proved that our proposed method achieved this high accuracy even if the testing images are rotated in various angles.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
2018-04-06T13:25:52Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/16734
url http://hdl.handle.net/10198/16734
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Monteiro, Fernando C. (2016). Automatic cattle identification using graph matching based on local invariant features. In International Conference in Image Analysis and Recognition - ICIAR 2016. Póvoa de Varzim, Portugal
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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