Application of the fuzzy logic in content-based image retrieval

Autores
Xiaoling, Wang; Kanglin, Xie
Año de publicación
2005
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.
Facultad de Informática
Materia
Ciencias Informáticas
fuzzy inference
Percepción Visual
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9504
Acceder
id SEDICI_a800483fca916feaf4627282fe3e2746
oai_identifier_str oai:sedici.unlp.edu.ar:10915/9504
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Application of the fuzzy logic in content-based image retrievalXiaoling, WangKanglin, XieCiencias Informáticasfuzzy inferencePercepción VisualThis paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.Facultad de Informática2005-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf19-24http://sedici.unlp.edu.ar/handle/10915/9504enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr05-4.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:44Zoai:sedici.unlp.edu.ar:10915/9504Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:44.225SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Application of the fuzzy logic in content-based image retrieval
title Application of the fuzzy logic in content-based image retrieval
spellingShingle Application of the fuzzy logic in content-based image retrieval
Xiaoling, Wang
Ciencias Informáticas
fuzzy inference
Percepción Visual
title_short Application of the fuzzy logic in content-based image retrieval
title_full Application of the fuzzy logic in content-based image retrieval
title_fullStr Application of the fuzzy logic in content-based image retrieval
title_full_unstemmed Application of the fuzzy logic in content-based image retrieval
title_sort Application of the fuzzy logic in content-based image retrieval
dc.creator.none.fl_str_mv Xiaoling, Wang
Kanglin, Xie
author Xiaoling, Wang
author_facet Xiaoling, Wang
Kanglin, Xie
author_role author
author2 Kanglin, Xie
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
fuzzy inference
Percepción Visual
topic Ciencias Informáticas
fuzzy inference
Percepción Visual
dc.description.none.fl_txt_mv This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.
Facultad de Informática
description This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image features, not the features themselves; secondly making use of the fuzzy inference to instruct the weights assignment among various image features; thirdly expressing the subjectivity of human perceptions by fuzzy rules impliedly; lastly we propose an improvement on the traditional histogram called the Average Area Histogram (AAH) to represent color features. Experimentally we realized a fuzzy logic-based image retrieval system with good retrieval performance.
publishDate 2005
dc.date.none.fl_str_mv 2005-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9504
url http://sedici.unlp.edu.ar/handle/10915/9504
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr05-4.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
19-24
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.070432

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