Color measurement: comparison of colorimeter vs. computer vision system

Autores
Goñi, Sandro Mauricio; Salvadori, Viviana Olga
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The aim of this work was to compare two food color measurement techniques, the traditional tristimulus colorimeter and an image analysis system. In this sense a computer vision system was developed, consisting of a digital camera, a controlled illumination environment, and a software package to process the images. The conversion between color spaces was performed employing empirical mathematical models; a standard color chart was used for its calibration. The color of 40 samples of raw and processed foods was measured in the CIELAB color space with the computer vision system and a colorimeter. The equivalence between both techniques, for individual L*, a* and b* values, was determined using appropriate hypothesis tests. For most samples both systems provide equivalent results, although the total color difference ΔΕ was high enough to be noticeable. The average ΔΕ was 5.88 ± 3.32, with an average absolute ΔL* = 2.79 ± 2.42, Δa* = 3.02 ± 2.94; Δb* = 2.84 ± 2.53. In addition, the color measured by the image analyses technique seemed to be more similar to the real ones.
Centro de Investigación y Desarrollo en Criotecnología de Alimentos
Materia
Química
Food color
Computer vision
Digital images
Image processing
Color calibration
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/103350

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spelling Color measurement: comparison of colorimeter vs. computer vision systemGoñi, Sandro MauricioSalvadori, Viviana OlgaQuímicaFood colorComputer visionDigital imagesImage processingColor calibrationThe aim of this work was to compare two food color measurement techniques, the traditional tristimulus colorimeter and an image analysis system. In this sense a computer vision system was developed, consisting of a digital camera, a controlled illumination environment, and a software package to process the images. The conversion between color spaces was performed employing empirical mathematical models; a standard color chart was used for its calibration. The color of 40 samples of raw and processed foods was measured in the CIELAB color space with the computer vision system and a colorimeter. The equivalence between both techniques, for individual L*, a* and b* values, was determined using appropriate hypothesis tests. For most samples both systems provide equivalent results, although the total color difference ΔΕ was high enough to be noticeable. The average ΔΕ was 5.88 ± 3.32, with an average absolute ΔL* = 2.79 ± 2.42, Δa* = 3.02 ± 2.94; Δb* = 2.84 ± 2.53. In addition, the color measured by the image analyses technique seemed to be more similar to the real ones.Centro de Investigación y Desarrollo en Criotecnología de Alimentos2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf538–547http://sedici.unlp.edu.ar/handle/10915/103350enginfo:eu-repo/semantics/altIdentifier/issn/2193-4134info:eu-repo/semantics/altIdentifier/doi/10.1007/s11694-016-9421-1info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:05:09Zoai:sedici.unlp.edu.ar:10915/103350Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:05:10.097SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Color measurement: comparison of colorimeter vs. computer vision system
title Color measurement: comparison of colorimeter vs. computer vision system
spellingShingle Color measurement: comparison of colorimeter vs. computer vision system
Goñi, Sandro Mauricio
Química
Food color
Computer vision
Digital images
Image processing
Color calibration
title_short Color measurement: comparison of colorimeter vs. computer vision system
title_full Color measurement: comparison of colorimeter vs. computer vision system
title_fullStr Color measurement: comparison of colorimeter vs. computer vision system
title_full_unstemmed Color measurement: comparison of colorimeter vs. computer vision system
title_sort Color measurement: comparison of colorimeter vs. computer vision system
dc.creator.none.fl_str_mv Goñi, Sandro Mauricio
Salvadori, Viviana Olga
author Goñi, Sandro Mauricio
author_facet Goñi, Sandro Mauricio
Salvadori, Viviana Olga
author_role author
author2 Salvadori, Viviana Olga
author2_role author
dc.subject.none.fl_str_mv Química
Food color
Computer vision
Digital images
Image processing
Color calibration
topic Química
Food color
Computer vision
Digital images
Image processing
Color calibration
dc.description.none.fl_txt_mv The aim of this work was to compare two food color measurement techniques, the traditional tristimulus colorimeter and an image analysis system. In this sense a computer vision system was developed, consisting of a digital camera, a controlled illumination environment, and a software package to process the images. The conversion between color spaces was performed employing empirical mathematical models; a standard color chart was used for its calibration. The color of 40 samples of raw and processed foods was measured in the CIELAB color space with the computer vision system and a colorimeter. The equivalence between both techniques, for individual L*, a* and b* values, was determined using appropriate hypothesis tests. For most samples both systems provide equivalent results, although the total color difference ΔΕ was high enough to be noticeable. The average ΔΕ was 5.88 ± 3.32, with an average absolute ΔL* = 2.79 ± 2.42, Δa* = 3.02 ± 2.94; Δb* = 2.84 ± 2.53. In addition, the color measured by the image analyses technique seemed to be more similar to the real ones.
Centro de Investigación y Desarrollo en Criotecnología de Alimentos
description The aim of this work was to compare two food color measurement techniques, the traditional tristimulus colorimeter and an image analysis system. In this sense a computer vision system was developed, consisting of a digital camera, a controlled illumination environment, and a software package to process the images. The conversion between color spaces was performed employing empirical mathematical models; a standard color chart was used for its calibration. The color of 40 samples of raw and processed foods was measured in the CIELAB color space with the computer vision system and a colorimeter. The equivalence between both techniques, for individual L*, a* and b* values, was determined using appropriate hypothesis tests. For most samples both systems provide equivalent results, although the total color difference ΔΕ was high enough to be noticeable. The average ΔΕ was 5.88 ± 3.32, with an average absolute ΔL* = 2.79 ± 2.42, Δa* = 3.02 ± 2.94; Δb* = 2.84 ± 2.53. In addition, the color measured by the image analyses technique seemed to be more similar to the real ones.
publishDate 2017
dc.date.none.fl_str_mv 2017
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info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/103350
url http://sedici.unlp.edu.ar/handle/10915/103350
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2193-4134
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11694-016-9421-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
538–547
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instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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