Parallelization of image similarity analysis

Autores
Naiouf, Marcelo; Tarrío, Diego F.; De Giusti, Armando Eduardo; De Giusti, Laura Cristina
Año de publicación
2001
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the most representative coefficients of the wavelet transform of the corresponding image area. In the present paper, image representation by wavelet transform coefficients is analyzed, as well as the convenience/necessity of using multiple coefficients for the study of similarity of images which may have transferred components, with change of sizes, color or texture. The complexity of the involved computation justifies parallelization, and the suggested solution constitutes a combination of a multiprocessors "pipelining", being each of them an homogeneous parallel architecture which obtains signature coefficients (wavelet). Partial reusability of computations for successive signatures makes these architectures pipelining compulsory.
Facultad de Informática
Materia
Ciencias Informáticas
Parallel algorithms
PATTERN RECOGNITION
Parallel processors
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:10915/9421
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/9421
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Parallelization of image similarity analysisNaiouf, MarceloTarrío, Diego F.De Giusti, Armando EduardoDe Giusti, Laura CristinaCiencias InformáticasParallel algorithmsPATTERN RECOGNITIONParallel processorsThe algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the most representative coefficients of the wavelet transform of the corresponding image area. In the present paper, image representation by wavelet transform coefficients is analyzed, as well as the convenience/necessity of using multiple coefficients for the study of similarity of images which may have transferred components, with change of sizes, color or texture. The complexity of the involved computation justifies parallelization, and the suggested solution constitutes a combination of a multiprocessors "pipelining", being each of them an homogeneous parallel architecture which obtains signature coefficients (wavelet). Partial reusability of computations for successive signatures makes these architectures pipelining compulsory.Facultad de Informática2001info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/9421enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/p7.pdfinfo: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:UNLP2025-09-29T10:50:40Zoai:sedici.unlp.edu.ar:10915/9421Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:40.328SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Parallelization of image similarity analysis
title Parallelization of image similarity analysis
spellingShingle Parallelization of image similarity analysis
Naiouf, Marcelo
Ciencias Informáticas
Parallel algorithms
PATTERN RECOGNITION
Parallel processors
title_short Parallelization of image similarity analysis
title_full Parallelization of image similarity analysis
title_fullStr Parallelization of image similarity analysis
title_full_unstemmed Parallelization of image similarity analysis
title_sort Parallelization of image similarity analysis
dc.creator.none.fl_str_mv Naiouf, Marcelo
Tarrío, Diego F.
De Giusti, Armando Eduardo
De Giusti, Laura Cristina
author Naiouf, Marcelo
author_facet Naiouf, Marcelo
Tarrío, Diego F.
De Giusti, Armando Eduardo
De Giusti, Laura Cristina
author_role author
author2 Tarrío, Diego F.
De Giusti, Armando Eduardo
De Giusti, Laura Cristina
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel algorithms
PATTERN RECOGNITION
Parallel processors
topic Ciencias Informáticas
Parallel algorithms
PATTERN RECOGNITION
Parallel processors
dc.description.none.fl_txt_mv The algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the most representative coefficients of the wavelet transform of the corresponding image area. In the present paper, image representation by wavelet transform coefficients is analyzed, as well as the convenience/necessity of using multiple coefficients for the study of similarity of images which may have transferred components, with change of sizes, color or texture. The complexity of the involved computation justifies parallelization, and the suggested solution constitutes a combination of a multiprocessors "pipelining", being each of them an homogeneous parallel architecture which obtains signature coefficients (wavelet). Partial reusability of computations for successive signatures makes these architectures pipelining compulsory.
Facultad de Informática
description The algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the most representative coefficients of the wavelet transform of the corresponding image area. In the present paper, image representation by wavelet transform coefficients is analyzed, as well as the convenience/necessity of using multiple coefficients for the study of similarity of images which may have transferred components, with change of sizes, color or texture. The complexity of the involved computation justifies parallelization, and the suggested solution constitutes a combination of a multiprocessors "pipelining", being each of them an homogeneous parallel architecture which obtains signature coefficients (wavelet). Partial reusability of computations for successive signatures makes these architectures pipelining compulsory.
publishDate 2001
dc.date.none.fl_str_mv 2001
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/10915/9421
url http://sedici.unlp.edu.ar/handle/10915/9421
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/p7.pdf
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
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 13.069144

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