Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images

One objective for classifying pixels belonging to specific textures in natural images is to achieve the best performance in classification as possible. We propose a new unsupervised hybrid classifier. The base classifiers for hybridization are the Fuzzy Clustering and the parametric Bayesian, both s...

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Detalles Bibliográficos
Autores: Cruz García, Jesús Manuel de la, Guijarro Mata-García, María, Pajares Martínsanz, Gonzalo, Herrera Caro, Pedro Javier
Tipo de recurso: capítulo de libro
Fecha de publicación:2011
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/45466
Acceso en línea:https://hdl.handle.net/20.500.14352/45466
Access Level:acceso abierto
Palabra clave:004
Classifier Combination
Fuzzy Aggregation
Parametric Estimation
Fuzzy Clustering
Bayes Classifier
Informática (Informática)
1203.17 Informática
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oai_identifier_str oai:docta.ucm.es:20.500.14352/45466
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repository_id_str
spelling Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in imagesCruz García, Jesús Manuel de laGuijarro Mata-García, MaríaPajares Martínsanz, GonzaloHerrera Caro, Pedro Javier004Classifier CombinationFuzzy AggregationParametric EstimationFuzzy ClusteringBayes ClassifierInformática (Informática)1203.17 InformáticaOne objective for classifying pixels belonging to specific textures in natural images is to achieve the best performance in classification as possible. We propose a new unsupervised hybrid classifier. The base classifiers for hybridization are the Fuzzy Clustering and the parametric Bayesian, both supervised and selected by their well-tested performance, as reported in the literature. During the training phase we estimate the parameters of each classifier. During the decision phase we apply fuzzy aggregation operators for making the hybridization. The design of the unsupervised classifier from supervised base classifiers and the automatic computation of the final decision with fuzzy aggregation operations, make the main contributions of this paper.Springer-Verlag BerlínUniversidad Complutense de Madrid20112011-01-0120112011-01-01book parthttp://purl.org/coar/resource_type/c_3248info:eu-repo/semantics/bookPartapplication/pdfhttps://hdl.handle.net/20.500.14352/45466reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/454662026-06-02T12:44:21Z
dc.title.none.fl_str_mv Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
title Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
spellingShingle Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
Cruz García, Jesús Manuel de la
004
Classifier Combination
Fuzzy Aggregation
Parametric Estimation
Fuzzy Clustering
Bayes Classifier
Informática (Informática)
1203.17 Informática
title_short Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
title_full Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
title_fullStr Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
title_full_unstemmed Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
title_sort Performance analysis of fuzzy aggregation operations for combining classifiers for natural textures in images
dc.creator.none.fl_str_mv Cruz García, Jesús Manuel de la
Guijarro Mata-García, María
Pajares Martínsanz, Gonzalo
Herrera Caro, Pedro Javier
author Cruz García, Jesús Manuel de la
author_facet Cruz García, Jesús Manuel de la
Guijarro Mata-García, María
Pajares Martínsanz, Gonzalo
Herrera Caro, Pedro Javier
author_role author
author2 Guijarro Mata-García, María
Pajares Martínsanz, Gonzalo
Herrera Caro, Pedro Javier
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004
Classifier Combination
Fuzzy Aggregation
Parametric Estimation
Fuzzy Clustering
Bayes Classifier
Informática (Informática)
1203.17 Informática
topic 004
Classifier Combination
Fuzzy Aggregation
Parametric Estimation
Fuzzy Clustering
Bayes Classifier
Informática (Informática)
1203.17 Informática
description One objective for classifying pixels belonging to specific textures in natural images is to achieve the best performance in classification as possible. We propose a new unsupervised hybrid classifier. The base classifiers for hybridization are the Fuzzy Clustering and the parametric Bayesian, both supervised and selected by their well-tested performance, as reported in the literature. During the training phase we estimate the parameters of each classifier. During the decision phase we apply fuzzy aggregation operators for making the hybridization. The design of the unsupervised classifier from supervised base classifiers and the automatic computation of the final decision with fuzzy aggregation operations, make the main contributions of this paper.
publishDate 2011
dc.date.none.fl_str_mv 2011
2011-01-01
2011
2011-01-01
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/45466
url https://hdl.handle.net/20.500.14352/45466
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer-Verlag Berlín
publisher.none.fl_str_mv Springer-Verlag Berlín
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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