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Calibrated color measurements of agricultural foods using image analysis

Mendoza, Fernando LU ; Dejmek, Petr LU orcid and Aguilera, Jose (2006) In Postharvest Biology and Technology 41(3). p.285-295
Abstract
A computer vision system (CVS) was implemented to quantify standard color of fruit and vegetables in sRGB, HSV and L*a*b* color spaces, and image capture conditions affecting the results were evaluated. These three color spaces are compared in terms of their suitability for color quantification in curved surfaces. The results show that sRGB standard (linear signals) was efficient to define the mapping between R'G'B' (no-linear signals) from the CCD camera and a device-independent system such as CIE XYZ. The CVS showed to be robust to changes in sample orientation, resolution, and zoom. However, the measured average color was shown to be significantly affected by the properties of the background and by the surface curvature and gloss. Thus... (More)
A computer vision system (CVS) was implemented to quantify standard color of fruit and vegetables in sRGB, HSV and L*a*b* color spaces, and image capture conditions affecting the results were evaluated. These three color spaces are compared in terms of their suitability for color quantification in curved surfaces. The results show that sRGB standard (linear signals) was efficient to define the mapping between R'G'B' (no-linear signals) from the CCD camera and a device-independent system such as CIE XYZ. The CVS showed to be robust to changes in sample orientation, resolution, and zoom. However, the measured average color was shown to be significantly affected by the properties of the background and by the surface curvature and gloss. Thus all average color results should be interpreted with caution. L*a*b* system is suggested as the best color space for quantification in foods with curved surfaces. (C) 2006 Elsevier B.V. All rights reserved. (Less)
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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
computer vision sensitivity, sRGB standard, CIE color, curved surfaces
in
Postharvest Biology and Technology
volume
41
issue
3
pages
285 - 295
publisher
Elsevier
external identifiers
  • wos:000240385900008
  • scopus:33751103926
ISSN
0925-5214
DOI
10.1016/j.postharvbio.2006.04.004
language
English
LU publication?
yes
id
45b42671-002d-456b-82e1-311a2379ce57 (old id 394342)
date added to LUP
2016-04-01 16:30:48
date last changed
2021-09-29 04:51:59
@article{45b42671-002d-456b-82e1-311a2379ce57,
  abstract     = {A computer vision system (CVS) was implemented to quantify standard color of fruit and vegetables in sRGB, HSV and L*a*b* color spaces, and image capture conditions affecting the results were evaluated. These three color spaces are compared in terms of their suitability for color quantification in curved surfaces. The results show that sRGB standard (linear signals) was efficient to define the mapping between R'G'B' (no-linear signals) from the CCD camera and a device-independent system such as CIE XYZ. The CVS showed to be robust to changes in sample orientation, resolution, and zoom. However, the measured average color was shown to be significantly affected by the properties of the background and by the surface curvature and gloss. Thus all average color results should be interpreted with caution. L*a*b* system is suggested as the best color space for quantification in foods with curved surfaces. (C) 2006 Elsevier B.V. All rights reserved.},
  author       = {Mendoza, Fernando and Dejmek, Petr and Aguilera, Jose},
  issn         = {0925-5214},
  language     = {eng},
  number       = {3},
  pages        = {285--295},
  publisher    = {Elsevier},
  series       = {Postharvest Biology and Technology},
  title        = {Calibrated color measurements of agricultural foods using image analysis},
  url          = {http://dx.doi.org/10.1016/j.postharvbio.2006.04.004},
  doi          = {10.1016/j.postharvbio.2006.04.004},
  volume       = {41},
  year         = {2006},
}