Superpixels extraction by an Intuitionistic fuzzy clustering algorithm

A scheme to develop the image over-segmentation task is introduced in this paper, it considers the pixels of an image as intuitive fuzzy sets and develops an intuitionistic clustering process of them. In this regard, the main contribution is to provide a method for extracting superpixels with greate...

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Detalles Bibliográficos
Autor: Dante Mújica-Vargas
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:México
Institución:Tecnológico Nacional de México
Repositorio:Redalyc-TNM
OAI Identifier:oai:redalyc.org:47471684005
Acceso en línea:https://www.redalyc.org/articulo.oa?id=47471684005
https://www.redalyc.org/journal/474/47471684005/
https://www.redalyc.org/journal/474/47471684005/html/
https://www.redalyc.org/journal/474/47471684005/47471684005.epub
https://www.redalyc.org/journal/474/47471684005/movil
Access Level:acceso abierto
Palabra clave:Ingeniería
Superpixels extraction
intuitionistic fuzzy clustering
biomedical grayscale and natural color images
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spelling Superpixels extraction by an Intuitionistic fuzzy clustering algorithmDante Mújica-VargasIngenieríaSuperpixels extractionintuitionistic fuzzy clusteringbiomedical grayscale and natural color imagesA scheme to develop the image over-segmentation task is introduced in this paper, it considers the pixels of an image as intuitive fuzzy sets and develops an intuitionistic clustering process of them. In this regard, the main contribution is to provide a method for extracting superpixels with greater adherence to the edges of the regions. Experimental tests were developed considering biomedical grayscale and natural color images. The robustness and effectiveness of this proposal was verified by quantitative and qualitative results.Universidad Nacional Autónoma de México2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf1665-6423https://www.redalyc.org/articulo.oa?id=47471684005https://www.redalyc.org/journal/474/47471684005/https://www.redalyc.org/journal/474/47471684005/html/https://www.redalyc.org/journal/474/47471684005/47471684005.epubhttps://www.redalyc.org/journal/474/47471684005/movil10.14482/INDES.30.1.303.661Journal of Applied Research and Technology (México) Num.2 Vol.19reponame:Redalyc-TNMinstname:Tecnológico Nacional de Méxicoinstacron:TNMenhttp://www.redalyc.org/revista.oa?id=474Journal of Applied Research and Technologyinfo:eu-repo/semantics/openAccessoai:redalyc.org:474716840052024-08-23T20:49:15Z
dc.title.none.fl_str_mv Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
title Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
spellingShingle Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
Dante Mújica-Vargas
Ingeniería
Superpixels extraction
intuitionistic fuzzy clustering
biomedical grayscale and natural color images
title_short Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
title_full Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
title_fullStr Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
title_full_unstemmed Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
title_sort Superpixels extraction by an Intuitionistic fuzzy clustering algorithm
dc.creator.none.fl_str_mv Dante Mújica-Vargas
author Dante Mújica-Vargas
author_facet Dante Mújica-Vargas
author_role author
dc.subject.none.fl_str_mv Ingeniería
Superpixels extraction
intuitionistic fuzzy clustering
biomedical grayscale and natural color images
topic Ingeniería
Superpixels extraction
intuitionistic fuzzy clustering
biomedical grayscale and natural color images
description A scheme to develop the image over-segmentation task is introduced in this paper, it considers the pixels of an image as intuitive fuzzy sets and develops an intuitionistic clustering process of them. In this regard, the main contribution is to provide a method for extracting superpixels with greater adherence to the edges of the regions. Experimental tests were developed considering biomedical grayscale and natural color images. The robustness and effectiveness of this proposal was verified by quantitative and qualitative results.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 1665-6423
https://www.redalyc.org/articulo.oa?id=47471684005
https://www.redalyc.org/journal/474/47471684005/
https://www.redalyc.org/journal/474/47471684005/html/
https://www.redalyc.org/journal/474/47471684005/47471684005.epub
https://www.redalyc.org/journal/474/47471684005/movil
10.14482/INDES.30.1.303.661
identifier_str_mv 1665-6423
10.14482/INDES.30.1.303.661
url https://www.redalyc.org/articulo.oa?id=47471684005
https://www.redalyc.org/journal/474/47471684005/
https://www.redalyc.org/journal/474/47471684005/html/
https://www.redalyc.org/journal/474/47471684005/47471684005.epub
https://www.redalyc.org/journal/474/47471684005/movil
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv http://www.redalyc.org/revista.oa?id=474
dc.rights.none.fl_str_mv Journal of Applied Research and Technology
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Journal of Applied Research and Technology
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional Autónoma de México
publisher.none.fl_str_mv Universidad Nacional Autónoma de México
dc.source.none.fl_str_mv Journal of Applied Research and Technology (México) Num.2 Vol.19
reponame:Redalyc-TNM
instname:Tecnológico Nacional de México
instacron:TNM
instname_str Tecnológico Nacional de México
instacron_str TNM
institution TNM
reponame_str Redalyc-TNM
collection Redalyc-TNM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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