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Determination of yarn production characteristics using image processing

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Detalhes bibliográficos
Resumo:This article describes a low-cost image acquisition and processing system, which measures several yarn production characteristics, namely, the fibers twist orientation, the folded yarn twist step, the folded yarn twist orientation, and the existence of single (nonfolded yarn) or multiple cables (folded yarn). The imaging hardware consists of a USB web camera coupled to an analog microscope and a monochromatic light source. The acquired images are analyzed using custom designed software based on the IMAQ Vision image program from National Instruments. A full description of the developed image processing tool is presented, together with several experimental results. The results obtained are consistent with information deduced from high-resolution images acquired using an electron microscope. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 391–399, 2010.
Autores principais:Carvalho, Vítor
Outros Autores:Belsley, M.; Vasconcelos, Rosa; Soares, Filomena
Assunto:Yarn production characteristics IMAQ vision System design
Ano:2010
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:This article describes a low-cost image acquisition and processing system, which measures several yarn production characteristics, namely, the fibers twist orientation, the folded yarn twist step, the folded yarn twist orientation, and the existence of single (nonfolded yarn) or multiple cables (folded yarn). The imaging hardware consists of a USB web camera coupled to an analog microscope and a monochromatic light source. The acquired images are analyzed using custom designed software based on the IMAQ Vision image program from National Instruments. A full description of the developed image processing tool is presented, together with several experimental results. The results obtained are consistent with information deduced from high-resolution images acquired using an electron microscope. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 391–399, 2010.