Computer vision system in real-time for color determination on flat surface food

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Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color m...

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Detalles Bibliográficos
Autores: Saldaña, Erick, Siche, Raul, Huamán, Rosmer, Luján, Mariano, Castro, Wilson, Quevedo, Roberto
Formato: artículo
Fecha de Publicación:2013
Institución:Universidad Nacional de Trujillo
Repositorio:Revista UNITRU - Scientia Agropecuaria
Lenguaje:inglés
OAI Identifier:oai:ojs.revistas.unitru.edu.pe:article/98
Enlace del recurso:http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98
Nivel de acceso:acceso abierto
Materia:Computer Vision
RGB model
CIELab model
food quality control
Matlab
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spelling Computer vision system in real-time for color determination on flat surface foodSaldaña, ErickSiche, RaulHuamán, RosmerLuján, MarianoCastro, WilsonQuevedo, RobertoComputer VisionRGB modelCIELab modelfood quality controlMatlabArtificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware), which consisted of two phases: a) image acquisition and b) image processing and analysis. Both the algorithm and the graphical interface (GUI) were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*), where were estimated the errors of the color parameters: eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector.Universidad Nacional de Trujillo2013-04-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/9810.17268/sci.agropecu.2013.01.06Scientia Agropecuaria; Vol. 4 No. 1 (2013): January - March; 55-63Scientia Agropecuaria; Vol. 4 Núm. 1 (2013): Enero - Marzo; 55-632306-67412077-9917reponame:Revista UNITRU - Scientia Agropecuariainstname:Universidad Nacional de Trujilloinstacron:UNITRUenghttp://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98/9Derechos de autor 2013 Scientia Agropecuariainfo:eu-repo/semantics/openAccess2021-06-01T15:35:14Zmail@mail.com -
dc.title.none.fl_str_mv Computer vision system in real-time for color determination on flat surface food
title Computer vision system in real-time for color determination on flat surface food
spellingShingle Computer vision system in real-time for color determination on flat surface food
Saldaña, Erick
Computer Vision
RGB model
CIELab model
food quality control
Matlab
title_short Computer vision system in real-time for color determination on flat surface food
title_full Computer vision system in real-time for color determination on flat surface food
title_fullStr Computer vision system in real-time for color determination on flat surface food
title_full_unstemmed Computer vision system in real-time for color determination on flat surface food
title_sort Computer vision system in real-time for color determination on flat surface food
dc.creator.none.fl_str_mv Saldaña, Erick
Siche, Raul
Huamán, Rosmer
Luján, Mariano
Castro, Wilson
Quevedo, Roberto
author Saldaña, Erick
author_facet Saldaña, Erick
Siche, Raul
Huamán, Rosmer
Luján, Mariano
Castro, Wilson
Quevedo, Roberto
author_role author
author2 Siche, Raul
Huamán, Rosmer
Luján, Mariano
Castro, Wilson
Quevedo, Roberto
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Computer Vision
RGB model
CIELab model
food quality control
Matlab
topic Computer Vision
RGB model
CIELab model
food quality control
Matlab
dc.description.none.fl_txt_mv Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware), which consisted of two phases: a) image acquisition and b) image processing and analysis. Both the algorithm and the graphical interface (GUI) were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*), where were estimated the errors of the color parameters: eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector.
description Artificial vision systems also known as computer vision are potent quality inspection tools, which can be applied in pattern recognition for fruits and vegetables analysis. The aim of this research was to design, implement and calibrate a new computer vision system (CVS) in real-time for the color measurement on flat surface food. For this purpose was designed and implemented a device capable of performing this task (software and hardware), which consisted of two phases: a) image acquisition and b) image processing and analysis. Both the algorithm and the graphical interface (GUI) were developed in Matlab. The CVS calibration was performed using a conventional colorimeter (Model CIEL* a* b*), where were estimated the errors of the color parameters: eL* = 5.001%, and ea* = 2.287%, and eb* = 4.314 % which ensure adequate and efficient automation application in industrial processes in the quality control in the food industry sector.
publishDate 2013
dc.date.none.fl_str_mv 2013-04-26
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98
10.17268/sci.agropecu.2013.01.06
url http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98
identifier_str_mv 10.17268/sci.agropecu.2013.01.06
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/98/9
dc.rights.none.fl_str_mv Derechos de autor 2013 Scientia Agropecuaria
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2013 Scientia Agropecuaria
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional de Trujillo
publisher.none.fl_str_mv Universidad Nacional de Trujillo
dc.source.none.fl_str_mv Scientia Agropecuaria; Vol. 4 No. 1 (2013): January - March; 55-63
Scientia Agropecuaria; Vol. 4 Núm. 1 (2013): Enero - Marzo; 55-63
2306-6741
2077-9917
reponame:Revista UNITRU - Scientia Agropecuaria
instname:Universidad Nacional de Trujillo
instacron:UNITRU
reponame_str Revista UNITRU - Scientia Agropecuaria
collection Revista UNITRU - Scientia Agropecuaria
instname_str Universidad Nacional de Trujillo
instacron_str UNITRU
institution UNITRU
repository.name.fl_str_mv -
repository.mail.fl_str_mv mail@mail.com
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