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Quantifying color variation: Improved formulas for calculating hue with segment classification(1)

• Premise of the study: Differences in color form a major component of biological variation, and quantifying these differences is the first step to understanding their evolutionary and ecological importance. One common method for measuring color variation is segment classification, which uses three...

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Detalles Bibliográficos
Autor principal: Smith, Stacey D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Botanical Society of America 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103106/
https://www.ncbi.nlm.nih.gov/pubmed/25202612
http://dx.doi.org/10.3732/apps.1300088
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author Smith, Stacey D.
author_facet Smith, Stacey D.
author_sort Smith, Stacey D.
collection PubMed
description • Premise of the study: Differences in color form a major component of biological variation, and quantifying these differences is the first step to understanding their evolutionary and ecological importance. One common method for measuring color variation is segment classification, which uses three variables (chroma, hue, and brightness) to describe the height and shape of reflectance curves. This study provides new formulas for calculating hue (the variable that describes the “type” of color) to give correct values in all regions of color space. • Methods and Results: Reflectance spectra were obtained from the literature, and chroma, hue, and brightness were computed for each spectrum using the original formulas as well as the new formulas. Only the new formulas result in correct values in the blue-green portion of color space. • Conclusions: Use of the new formulas for calculating hue will result in more accurate color quantification for a broad range of biological applications.
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spelling pubmed-41031062014-09-08 Quantifying color variation: Improved formulas for calculating hue with segment classification(1) Smith, Stacey D. Appl Plant Sci Protocol Note • Premise of the study: Differences in color form a major component of biological variation, and quantifying these differences is the first step to understanding their evolutionary and ecological importance. One common method for measuring color variation is segment classification, which uses three variables (chroma, hue, and brightness) to describe the height and shape of reflectance curves. This study provides new formulas for calculating hue (the variable that describes the “type” of color) to give correct values in all regions of color space. • Methods and Results: Reflectance spectra were obtained from the literature, and chroma, hue, and brightness were computed for each spectrum using the original formulas as well as the new formulas. Only the new formulas result in correct values in the blue-green portion of color space. • Conclusions: Use of the new formulas for calculating hue will result in more accurate color quantification for a broad range of biological applications. Botanical Society of America 2014-02-26 /pmc/articles/PMC4103106/ /pubmed/25202612 http://dx.doi.org/10.3732/apps.1300088 Text en © 2014 Smith. Published by the Botanical Society of America http://creativecommons.org/licenses/by-nc/4.0/ This work is licensed under a Creative Commons Attribution License (CC-BY-NC-SA).
spellingShingle Protocol Note
Smith, Stacey D.
Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title_full Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title_fullStr Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title_full_unstemmed Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title_short Quantifying color variation: Improved formulas for calculating hue with segment classification(1)
title_sort quantifying color variation: improved formulas for calculating hue with segment classification(1)
topic Protocol Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103106/
https://www.ncbi.nlm.nih.gov/pubmed/25202612
http://dx.doi.org/10.3732/apps.1300088
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