Color quantization with Particle swarm optimization and artificial ants

Proyecto financiado por la Fundación Memoria de D. Samuel Solórzano Barruso (FS/102015)

Detalles Bibliográficos
Autor: Pérez Delgado, María Luisa
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/161082
Acceso en línea:http://hdl.handle.net/10366/161082
Access Level:acceso abierto
Palabra clave:Color quantization
Artificial ants
Ant-tree algorithm
Particle swarm optimization algorithm
Clustering
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spelling Color quantization with Particle swarm optimization and artificial antsPérez Delgado, María LuisaColor quantizationArtificial antsAnt-tree algorithmParticle swarm optimization algorithmClusteringProyecto financiado por la Fundación Memoria de D. Samuel Solórzano Barruso (FS/102015)[EN]This article describes a color quantization algorithm that combines two swarm-based methods: Particle swarm optimization and artificial ants. The proposed method is based on a previous method that solves the quantization problem by combining the Particle swarm optimization algorithm with the K-means algorithm. K-means is a popular clustering method that has been applied to solve a variety of problems, including the color quantization problem. Nevertheless, it is a time-consuming method, which makes combining the Particle swarm optimization algorithm and K-means less suitable than other color quantization techniques. The proposed method, however, discards the K-means algorithm and applies the Ant-tree for color quantization algorithm in order to reduce execution time. This article shows that the new method outperforms the original one, since it requires less time to obtain higher quality images. In addition, the images produced are also of better quality than those produced by other well-known color quantization methods, such as Neuquant, Octree, Median-cut, Variance-based, Binary splitting and Wu’s methods.Springer202420242020info:eu-repo/semantics/articlehttp://hdl.handle.net/10366/161082reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)InglésFS/2015info:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1610822026-06-07T06:28:51Z
dc.title.none.fl_str_mv Color quantization with Particle swarm optimization and artificial ants
title Color quantization with Particle swarm optimization and artificial ants
spellingShingle Color quantization with Particle swarm optimization and artificial ants
Pérez Delgado, María Luisa
Color quantization
Artificial ants
Ant-tree algorithm
Particle swarm optimization algorithm
Clustering
title_short Color quantization with Particle swarm optimization and artificial ants
title_full Color quantization with Particle swarm optimization and artificial ants
title_fullStr Color quantization with Particle swarm optimization and artificial ants
title_full_unstemmed Color quantization with Particle swarm optimization and artificial ants
title_sort Color quantization with Particle swarm optimization and artificial ants
dc.creator.none.fl_str_mv Pérez Delgado, María Luisa
author Pérez Delgado, María Luisa
author_facet Pérez Delgado, María Luisa
author_role author
dc.subject.none.fl_str_mv Color quantization
Artificial ants
Ant-tree algorithm
Particle swarm optimization algorithm
Clustering
topic Color quantization
Artificial ants
Ant-tree algorithm
Particle swarm optimization algorithm
Clustering
description Proyecto financiado por la Fundación Memoria de D. Samuel Solórzano Barruso (FS/102015)
publishDate 2020
dc.date.none.fl_str_mv 2020
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/161082
url http://hdl.handle.net/10366/161082
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv FS/2015
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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