Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/42655

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Campo DCValorIdioma
dc.contributor.authorGonçalves, Nunopor
dc.contributor.authorCarvalho, Vítorpor
dc.contributor.authorBelsley, M.por
dc.contributor.authorVasconcelos, Rosapor
dc.contributor.authorSoares, Filomenapor
dc.contributor.authorMachado, Josépor
dc.date.accessioned2016-09-20T08:48:38Z-
dc.date.available2016-09-20T08:48:38Z-
dc.date.issued2015-
dc.date.submitted2014-
dc.identifier.issn0263-2241por
dc.identifier.urihttps://hdl.handle.net/1822/42655-
dc.description.abstractThe 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.por
dc.language.isoengpor
dc.publisherElsevier 1por
dc.rightsopenAccesspor
dc.subjectYarn linear masspor
dc.subjectYarn diameterpor
dc.subjectYarn hairinesspor
dc.subjectImage processingpor
dc.subjectComputer visionpor
dc.subjectIMAQ visionpor
dc.titleYarn features extraction using image processing and computer vision: a study with cotton and polyester yarnspor
dc.typearticlepor
dc.peerreviewedyespor
sdum.publicationstatusinfo:eu-repo/semantics/publishedVersionpor
oaire.citationStartPage1por
oaire.citationEndPage15por
oaire.citationTitleMeasurementpor
oaire.citationVolume68por
dc.identifier.doi10.1016/j.measurement.2015.02.010por
dc.subject.fosEngenharia e Tecnologia::Engenharia dos Materiaispor
sdum.journalMeasurementpor
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