Stream processing to solve image search by similarity

Autores
Lobos, Jair; Gil Costa, Graciela Verónica; Reyes, Nora Susana; Printista, Alicia Marcela; Marín, Mauricio
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.
Facultad de Informática
Materia
Ciencias Informáticas
stream processing
metrics spaces
MPEG-7
sparse spatial selection
Metrics
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/50180
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/50180
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Stream processing to solve image search by similarityLobos, JairGil Costa, Graciela VerónicaReyes, Nora SusanaPrintista, Alicia MarcelaMarín, MauricioCiencias Informáticasstream processingmetrics spacesMPEG-7sparse spatial selectionMetricsThe classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.Facultad de Informática2015-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf93-99http://sedici.unlp.edu.ar/handle/10915/50180enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST41-Paper-8.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:03:52Zoai:sedici.unlp.edu.ar:10915/50180Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:03:52.311SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Stream processing to solve image search by similarity
title Stream processing to solve image search by similarity
spellingShingle Stream processing to solve image search by similarity
Lobos, Jair
Ciencias Informáticas
stream processing
metrics spaces
MPEG-7
sparse spatial selection
Metrics
title_short Stream processing to solve image search by similarity
title_full Stream processing to solve image search by similarity
title_fullStr Stream processing to solve image search by similarity
title_full_unstemmed Stream processing to solve image search by similarity
title_sort Stream processing to solve image search by similarity
dc.creator.none.fl_str_mv Lobos, Jair
Gil Costa, Graciela Verónica
Reyes, Nora Susana
Printista, Alicia Marcela
Marín, Mauricio
author Lobos, Jair
author_facet Lobos, Jair
Gil Costa, Graciela Verónica
Reyes, Nora Susana
Printista, Alicia Marcela
Marín, Mauricio
author_role author
author2 Gil Costa, Graciela Verónica
Reyes, Nora Susana
Printista, Alicia Marcela
Marín, Mauricio
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
stream processing
metrics spaces
MPEG-7
sparse spatial selection
Metrics
topic Ciencias Informáticas
stream processing
metrics spaces
MPEG-7
sparse spatial selection
Metrics
dc.description.none.fl_txt_mv The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.
Facultad de Informática
description The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.
publishDate 2015
dc.date.none.fl_str_mv 2015-11
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/10915/50180
url http://sedici.unlp.edu.ar/handle/10915/50180
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/JCST41-Paper-8.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/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
93-99
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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