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A color extraction algorithm by segmentation

The segmentation and extraction on color features can provide useful information for many different application domains. However, most of the existing image processing algorithms on feature extraction are gray image-based and consider only one-dimensional parameters. In order to carry out a fast and...

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Detalles Bibliográficos
Autores principales: Wu, QingE, Fang, Zhenggaoyuan, Song, Zhichao, Chen, Hu, Lu, Yingbo, Zhou, Lintao, Qian, Xiaoliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692200/
https://www.ncbi.nlm.nih.gov/pubmed/38040896
http://dx.doi.org/10.1038/s41598-023-48689-y
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author Wu, QingE
Fang, Zhenggaoyuan
Song, Zhichao
Chen, Hu
Lu, Yingbo
Zhou, Lintao
Qian, Xiaoliang
author_facet Wu, QingE
Fang, Zhenggaoyuan
Song, Zhichao
Chen, Hu
Lu, Yingbo
Zhou, Lintao
Qian, Xiaoliang
author_sort Wu, QingE
collection PubMed
description The segmentation and extraction on color features can provide useful information for many different application domains. However, most of the existing image processing algorithms on feature extraction are gray image-based and consider only one-dimensional parameters. In order to carry out a fast and accurate color feature extraction, this paper proposes a color extraction algorithm by segmentation that is called a color extraction algorithm This algorithm is compared under different color distribution situations, and the extraction effect on color is also shown by the combination of the segmentation and feature extraction algorithms. Experimental results show that such segmentation algorithm has some advantages for color segmentation. In the fuzzy color image preprocessing, this paper gives the location method of region of interest. Moreover, compared with other existing extraction algorithms, the presented segmentation extraction algorithm in this paper not only has higher accuracy, shorter extraction time and stronger anti-interference ability, but also has better effect on more divergent color edge. Experimental evaluation of the proposed color extraction algorithm demonstrates dominance over existing algorithms for feature extraction. These researches in this paper provide a new way of thinking for color feature extraction by segmentation, which has an important theoretical references and practical significance.
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spelling pubmed-106922002023-12-03 A color extraction algorithm by segmentation Wu, QingE Fang, Zhenggaoyuan Song, Zhichao Chen, Hu Lu, Yingbo Zhou, Lintao Qian, Xiaoliang Sci Rep Article The segmentation and extraction on color features can provide useful information for many different application domains. However, most of the existing image processing algorithms on feature extraction are gray image-based and consider only one-dimensional parameters. In order to carry out a fast and accurate color feature extraction, this paper proposes a color extraction algorithm by segmentation that is called a color extraction algorithm This algorithm is compared under different color distribution situations, and the extraction effect on color is also shown by the combination of the segmentation and feature extraction algorithms. Experimental results show that such segmentation algorithm has some advantages for color segmentation. In the fuzzy color image preprocessing, this paper gives the location method of region of interest. Moreover, compared with other existing extraction algorithms, the presented segmentation extraction algorithm in this paper not only has higher accuracy, shorter extraction time and stronger anti-interference ability, but also has better effect on more divergent color edge. Experimental evaluation of the proposed color extraction algorithm demonstrates dominance over existing algorithms for feature extraction. These researches in this paper provide a new way of thinking for color feature extraction by segmentation, which has an important theoretical references and practical significance. Nature Publishing Group UK 2023-12-02 /pmc/articles/PMC10692200/ /pubmed/38040896 http://dx.doi.org/10.1038/s41598-023-48689-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wu, QingE
Fang, Zhenggaoyuan
Song, Zhichao
Chen, Hu
Lu, Yingbo
Zhou, Lintao
Qian, Xiaoliang
A color extraction algorithm by segmentation
title A color extraction algorithm by segmentation
title_full A color extraction algorithm by segmentation
title_fullStr A color extraction algorithm by segmentation
title_full_unstemmed A color extraction algorithm by segmentation
title_short A color extraction algorithm by segmentation
title_sort color extraction algorithm by segmentation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10692200/
https://www.ncbi.nlm.nih.gov/pubmed/38040896
http://dx.doi.org/10.1038/s41598-023-48689-y
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