Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/42655 |
Resumo: | The aim of this paper is the development of a new technological solution, for the automatic characterization of the yarn mass parameters (linear mass, diameter, and hairiness) based on image processing and computer vision techniques. A preliminary study for the detection and distinction between loop and protruding fibers is also presented. A custom-made application developed in LabVIEW from National Instruments with the IMAQ Vision Toolkit was used to acquire, analyze and process the yarn images. Some experimental results using cotton and polyester yarns were performed and compared with a commercial solution for validation. The presented approach allows a correct yarn parameterization improving products’ quality in the textile industry. |
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7160 |
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Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarnsYarn linear massYarn diameterYarn hairinessImage processingComputer visionIMAQ visionEngenharia e Tecnologia::Engenharia dos MateriaisThe aim of this paper is the development of a new technological solution, for the automatic characterization of the yarn mass parameters (linear mass, diameter, and hairiness) based on image processing and computer vision techniques. A preliminary study for the detection and distinction between loop and protruding fibers is also presented. A custom-made application developed in LabVIEW from National Instruments with the IMAQ Vision Toolkit was used to acquire, analyze and process the yarn images. Some experimental results using cotton and polyester yarns were performed and compared with a commercial solution for validation. The presented approach allows a correct yarn parameterization improving products’ quality in the textile industry.ElsevierUniversidade do MinhoGonçalves, NunoCarvalho, VítorBelsley, M.Vasconcelos, RosaSoares, FilomenaMachado, José20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/42655eng0263-224110.1016/j.measurement.2015.02.010info: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:RCAAP2023-07-21T12:25:36Zoai:repositorium.sdum.uminho.pt:1822/42655Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:19:51.632424Repositório 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 |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
title |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
spellingShingle |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns Gonçalves, Nuno Yarn linear mass Yarn diameter Yarn hairiness Image processing Computer vision IMAQ vision Engenharia e Tecnologia::Engenharia dos Materiais |
title_short |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
title_full |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
title_fullStr |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
title_full_unstemmed |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
title_sort |
Yarn features extraction using image processing and computer vision: a study with cotton and polyester yarns |
author |
Gonçalves, Nuno |
author_facet |
Gonçalves, Nuno Carvalho, Vítor Belsley, M. Vasconcelos, Rosa Soares, Filomena Machado, José |
author_role |
author |
author2 |
Carvalho, Vítor Belsley, M. Vasconcelos, Rosa Soares, Filomena Machado, José |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Gonçalves, Nuno Carvalho, Vítor Belsley, M. Vasconcelos, Rosa Soares, Filomena Machado, José |
dc.subject.por.fl_str_mv |
Yarn linear mass Yarn diameter Yarn hairiness Image processing Computer vision IMAQ vision Engenharia e Tecnologia::Engenharia dos Materiais |
topic |
Yarn linear mass Yarn diameter Yarn hairiness Image processing Computer vision IMAQ vision Engenharia e Tecnologia::Engenharia dos Materiais |
description |
The aim of this paper is the development of a new technological solution, for the automatic characterization of the yarn mass parameters (linear mass, diameter, and hairiness) based on image processing and computer vision techniques. A preliminary study for the detection and distinction between loop and protruding fibers is also presented. A custom-made application developed in LabVIEW from National Instruments with the IMAQ Vision Toolkit was used to acquire, analyze and process the yarn images. Some experimental results using cotton and polyester yarns were performed and compared with a commercial solution for validation. The presented approach allows a correct yarn parameterization improving products’ quality in the textile industry. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/42655 |
url |
http://hdl.handle.net/1822/42655 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0263-2241 10.1016/j.measurement.2015.02.010 |
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.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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 |
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1799132659326124032 |