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Improving Discrimination in Color Vision Deficiency by Image Re-Coloring

People with color vision deficiency (CVD) cannot observe the colorful world due to the damage of color reception nerves. In this work, we present an image enhancement approach to assist colorblind people to identify the colors they are not able to distinguish naturally. An image re-coloring algorith...

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Autores principales: Lin, Huei-Yung, Chen, Li-Qi, Wang, Min-Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567888/
https://www.ncbi.nlm.nih.gov/pubmed/31096676
http://dx.doi.org/10.3390/s19102250
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author Lin, Huei-Yung
Chen, Li-Qi
Wang, Min-Liang
author_facet Lin, Huei-Yung
Chen, Li-Qi
Wang, Min-Liang
author_sort Lin, Huei-Yung
collection PubMed
description People with color vision deficiency (CVD) cannot observe the colorful world due to the damage of color reception nerves. In this work, we present an image enhancement approach to assist colorblind people to identify the colors they are not able to distinguish naturally. An image re-coloring algorithm based on eigenvector processing is proposed for robust color separation under color deficiency transformation. It is shown that the eigenvector of color vision deficiency is distorted by an angle in the [Formula: see text] , Y-B, R-G color space. The experimental results show that our approach is useful for the recognition and separation of the CVD confusing colors in natural scene images. Compared to the existing techniques, our results of natural images with CVD simulation work very well in terms of RMS, HDR-VDP-2 and an IRB-approved human test. Both the objective comparison with previous works and the subjective evaluation on human tests validate the effectiveness of the proposed method.
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spelling pubmed-65678882019-06-17 Improving Discrimination in Color Vision Deficiency by Image Re-Coloring Lin, Huei-Yung Chen, Li-Qi Wang, Min-Liang Sensors (Basel) Article People with color vision deficiency (CVD) cannot observe the colorful world due to the damage of color reception nerves. In this work, we present an image enhancement approach to assist colorblind people to identify the colors they are not able to distinguish naturally. An image re-coloring algorithm based on eigenvector processing is proposed for robust color separation under color deficiency transformation. It is shown that the eigenvector of color vision deficiency is distorted by an angle in the [Formula: see text] , Y-B, R-G color space. The experimental results show that our approach is useful for the recognition and separation of the CVD confusing colors in natural scene images. Compared to the existing techniques, our results of natural images with CVD simulation work very well in terms of RMS, HDR-VDP-2 and an IRB-approved human test. Both the objective comparison with previous works and the subjective evaluation on human tests validate the effectiveness of the proposed method. MDPI 2019-05-15 /pmc/articles/PMC6567888/ /pubmed/31096676 http://dx.doi.org/10.3390/s19102250 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lin, Huei-Yung
Chen, Li-Qi
Wang, Min-Liang
Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title_full Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title_fullStr Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title_full_unstemmed Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title_short Improving Discrimination in Color Vision Deficiency by Image Re-Coloring
title_sort improving discrimination in color vision deficiency by image re-coloring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567888/
https://www.ncbi.nlm.nih.gov/pubmed/31096676
http://dx.doi.org/10.3390/s19102250
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