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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/103350
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article 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 |
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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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reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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