Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods

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=S0101-20612016000300499
Resumo: Abstract The colour of food is one of the most important factors affecting consumers’ purchasing decision. Although there are many colour spaces, the most widely used colour space in the food industry is L*a*b* colour space. Conventionally, the colour of foods is analysed with a colorimeter that measures small and non-representative areas of the food and the measurements usually vary depending on the point where the measurement is taken. This leads to the development of alternative colour analysis techniques. In this work, a simple and alternative method to measure the colour of foods known as “computer vision system” is presented and justified. With the aid of the computer vision system, foods that are homogenous and uniform in colour and shape could be classified with regard to their colours in a fast, inexpensive and simple way. This system could also be used to distinguish the defectives from the non-defectives. Quality parameters of meat and dairy products could be monitored without any physical contact, which causes contamination during sampling.
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spelling Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foodscomputer vision systemfoodRGBL*a*b*Abstract The colour of food is one of the most important factors affecting consumers’ purchasing decision. Although there are many colour spaces, the most widely used colour space in the food industry is L*a*b* colour space. Conventionally, the colour of foods is analysed with a colorimeter that measures small and non-representative areas of the food and the measurements usually vary depending on the point where the measurement is taken. This leads to the development of alternative colour analysis techniques. In this work, a simple and alternative method to measure the colour of foods known as “computer vision system” is presented and justified. With the aid of the computer vision system, foods that are homogenous and uniform in colour and shape could be classified with regard to their colours in a fast, inexpensive and simple way. This system could also be used to distinguish the defectives from the non-defectives. Quality parameters of meat and dairy products could be monitored without any physical contact, which causes contamination during sampling.Sociedade Brasileira de Ciência e Tecnologia de Alimentos2016-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000300499Food Science and Technology v.36 n.3 2016reponame:Food Science and Technology (Campinas)instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)instacron:SBCTA10.1590/1678-457X.02616info:eu-repo/semantics/openAccessTARLAK,FatihOZDEMİR,MuratMELİKOGLU,Mehmeteng2016-09-29T00:00:00Zoai:scielo:S0101-20612016000300499Revistahttp://www.scielo.br/ctaONGhttps://old.scielo.br/oai/scielo-oai.php||revista@sbcta.org.br1678-457X0101-2061opendoar:2016-09-29T00:00Food 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 II. validation of methodology with real foods
title Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
spellingShingle Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
TARLAK,Fatih
computer vision system
food
RGB
L*a*b*
title_short Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
title_full Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
title_fullStr Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
title_full_unstemmed Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
title_sort Computer vision system approach in colour measurements of foods: Part II. validation of methodology with real foods
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 computer vision system
food
RGB
L*a*b*
topic computer vision system
food
RGB
L*a*b*
description Abstract The colour of food is one of the most important factors affecting consumers’ purchasing decision. Although there are many colour spaces, the most widely used colour space in the food industry is L*a*b* colour space. Conventionally, the colour of foods is analysed with a colorimeter that measures small and non-representative areas of the food and the measurements usually vary depending on the point where the measurement is taken. This leads to the development of alternative colour analysis techniques. In this work, a simple and alternative method to measure the colour of foods known as “computer vision system” is presented and justified. With the aid of the computer vision system, foods that are homogenous and uniform in colour and shape could be classified with regard to their colours in a fast, inexpensive and simple way. This system could also be used to distinguish the defectives from the non-defectives. Quality parameters of meat and dairy products could be monitored without any physical contact, which causes contamination during sampling.
publishDate 2016
dc.date.none.fl_str_mv 2016-09-01
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=S0101-20612016000300499
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612016000300499
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-457X.02616
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.3 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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