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A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software
Color analysis of spalted wood surfaces requires a non-subjective, repeatable method for determining percent of pigmentation on the wood surface. Previously published methods used human visual perception with a square grid overlay to determine the percent of surface pigmentation. Our new method uses...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445697/ http://dx.doi.org/10.3390/ma2010062 |
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author | Robinson, Sara C. Laks, Peter E. Turnquist, Ethan J. |
author_facet | Robinson, Sara C. Laks, Peter E. Turnquist, Ethan J. |
author_sort | Robinson, Sara C. |
collection | PubMed |
description | Color analysis of spalted wood surfaces requires a non-subjective, repeatable method for determining percent of pigmentation on the wood surface. Previously published methods used human visual perception with a square grid overlay to determine the percent of surface pigmentation. Our new method uses Scion Image(©), a graphical software program used for grayscale and color analysis, to separate fungal pigments from the wood background. These human interface processes render the wood block into HSV (hue, saturation, value, within the RGB color space), allowing subtle and drastic color changes to be visualized, selected and analyzed by the software. Analysis with Scion Image(©) allows for a faster, less subjective, and easily repeatable procedure that is superior to simple human visual perception. |
format | Online Article Text |
id | pubmed-5445697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Molecular Diversity Preservation International |
record_format | MEDLINE/PubMed |
spelling | pubmed-54456972017-07-28 A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software Robinson, Sara C. Laks, Peter E. Turnquist, Ethan J. Materials (Basel) Article Color analysis of spalted wood surfaces requires a non-subjective, repeatable method for determining percent of pigmentation on the wood surface. Previously published methods used human visual perception with a square grid overlay to determine the percent of surface pigmentation. Our new method uses Scion Image(©), a graphical software program used for grayscale and color analysis, to separate fungal pigments from the wood background. These human interface processes render the wood block into HSV (hue, saturation, value, within the RGB color space), allowing subtle and drastic color changes to be visualized, selected and analyzed by the software. Analysis with Scion Image(©) allows for a faster, less subjective, and easily repeatable procedure that is superior to simple human visual perception. Molecular Diversity Preservation International 2009-02-16 /pmc/articles/PMC5445697/ http://dx.doi.org/10.3390/ma2010062 Text en © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Robinson, Sara C. Laks, Peter E. Turnquist, Ethan J. A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title | A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title_full | A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title_fullStr | A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title_full_unstemmed | A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title_short | A Method for Digital Color Analysis of Spalted Wood Using Scion Image Software |
title_sort | method for digital color analysis of spalted wood using scion image software |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5445697/ http://dx.doi.org/10.3390/ma2010062 |
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