Computer vision system approach in colour measurements of foods: Part I. development of methodology

Detalhes bibliográficos
Autor(a) principal: TARLAK,Fatih
Data de Publicação: 2016
Outros Autores: OZDEMİR,Murat, MELİKOGLU,Mehmet
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Food Science and Technology (Campinas)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000200382
Resumo: Abstract The colour assessment ability of the computer vision system is investigated and the data are compared with colour measurements taken by a conventional colorimeter. Linear and quadratic models are built to improve currently used methodology for the conversion of RGB colour units to L * a * b * colour space. For this purpose, two innovative ideas are proposed and tested. First, substantial amount of colour tones is generated to cover as many points in the colour space as possible. Secondly, the colour space is calibrated separately, whereas in previous research in the literature, the colour space is calibrated simultaneously. It is found that the RGB colour units to L * a * b * colour space transformation approach proposed in this study is more logical and more accurate, and the prediction performance of the quadratic model is superior over the linear model.
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spelling Computer vision system approach in colour measurements of foods: Part I. development of methodologycolourcomputer vision systemcolorimeterRGBL* a* b*Abstract The colour assessment ability of the computer vision system is investigated and the data are compared with colour measurements taken by a conventional colorimeter. Linear and quadratic models are built to improve currently used methodology for the conversion of RGB colour units to L * a * b * colour space. For this purpose, two innovative ideas are proposed and tested. First, substantial amount of colour tones is generated to cover as many points in the colour space as possible. Secondly, the colour space is calibrated separately, whereas in previous research in the literature, the colour space is calibrated simultaneously. It is found that the RGB colour units to L * a * b * colour space transformation approach proposed in this study is more logical and more accurate, and the prediction performance of the quadratic model is superior over the linear model.Sociedade Brasileira de Ciência e Tecnologia de Alimentos2016-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000200382Food Science and Technology v.36 n.2 2016reponame:Food Science and Technology (Campinas)instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)instacron:SBCTA10.1590/1678-457X.11615info:eu-repo/semantics/openAccessTARLAK,FatihOZDEMİR,MuratMELİKOGLU,Mehmeteng2016-07-08T00:00:00Zoai:scielo:S0101-20612016000200382Revistahttp://www.scielo.br/ctaONGhttps://old.scielo.br/oai/scielo-oai.php||revista@sbcta.org.br1678-457X0101-2061opendoar:2016-07-08T00:00Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)false
dc.title.none.fl_str_mv Computer vision system approach in colour measurements of foods: Part I. development of methodology
title Computer vision system approach in colour measurements of foods: Part I. development of methodology
spellingShingle Computer vision system approach in colour measurements of foods: Part I. development of methodology
TARLAK,Fatih
colour
computer vision system
colorimeter
RGB
L* a* b*
title_short Computer vision system approach in colour measurements of foods: Part I. development of methodology
title_full Computer vision system approach in colour measurements of foods: Part I. development of methodology
title_fullStr Computer vision system approach in colour measurements of foods: Part I. development of methodology
title_full_unstemmed Computer vision system approach in colour measurements of foods: Part I. development of methodology
title_sort Computer vision system approach in colour measurements of foods: Part I. development of methodology
author TARLAK,Fatih
author_facet TARLAK,Fatih
OZDEMİR,Murat
MELİKOGLU,Mehmet
author_role author
author2 OZDEMİR,Murat
MELİKOGLU,Mehmet
author2_role author
author
dc.contributor.author.fl_str_mv TARLAK,Fatih
OZDEMİR,Murat
MELİKOGLU,Mehmet
dc.subject.por.fl_str_mv colour
computer vision system
colorimeter
RGB
L* a* b*
topic colour
computer vision system
colorimeter
RGB
L* a* b*
description Abstract The colour assessment ability of the computer vision system is investigated and the data are compared with colour measurements taken by a conventional colorimeter. Linear and quadratic models are built to improve currently used methodology for the conversion of RGB colour units to L * a * b * colour space. For this purpose, two innovative ideas are proposed and tested. First, substantial amount of colour tones is generated to cover as many points in the colour space as possible. Secondly, the colour space is calibrated separately, whereas in previous research in the literature, the colour space is calibrated simultaneously. It is found that the RGB colour units to L * a * b * colour space transformation approach proposed in this study is more logical and more accurate, and the prediction performance of the quadratic model is superior over the linear model.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000200382
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000200382
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-457X.11615
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência e Tecnologia de Alimentos
publisher.none.fl_str_mv Sociedade Brasileira de Ciência e Tecnologia de Alimentos
dc.source.none.fl_str_mv Food Science and Technology v.36 n.2 2016
reponame:Food Science and Technology (Campinas)
instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron:SBCTA
instname_str Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
instacron_str SBCTA
institution SBCTA
reponame_str Food Science and Technology (Campinas)
collection Food Science and Technology (Campinas)
repository.name.fl_str_mv Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)
repository.mail.fl_str_mv ||revista@sbcta.org.br
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