Automatic and online setting of similarity thresholds in content-based visual information retrieval problems.
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/7167 http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16 |
Resumo: | Several information recovery systems use functions to determine similarity among objects in a collection. Such functions require a similarity threshold, from which it becomes possible to decide on the similarity between two given objects. Thus, depending on its value, the results returned by systems in a search may be satisfactory or not. However, the definition of similarity thresholds is difficult because it depends on several factors. Typically, specialists fix a threshold value for a given system, which is used in all searches. However, an expert-defined value is quite costly and not always possible. Therefore, this study proposes an approach for automatic and online estimation of the similarity threshold value, to be specifically used by content-based visual information retrieval system (image and video) search engines. The experimental results obtained with the proposed approach prove rather promising. For example, for one of the case studies, the performance of the proposed approach achieved 99.5 % efficiency in comparison with that obtained by a specialist using an empirical similarity threshold. Moreover, such automated approach becomes more scalable and less costly. |
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Bessas, Izaquiel L.Pádua, Flávio Luis CardealAssis, Guilherme Tavares deCardoso, Rodrigo T. N.Lacerda, Anisio Mendes2017-02-01T12:46:05Z2017-02-01T12:46:05Z2016BESSAS, I. L. et al. Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. EURASIP Journal on Advances in Signal Processing, v. 2016, n. 32, p. 1-16, 2016. Disponível em: <http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16>. Acesso em: 20 jan. 2017.16876180http://www.repositorio.ufop.br/handle/123456789/7167http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16Several information recovery systems use functions to determine similarity among objects in a collection. Such functions require a similarity threshold, from which it becomes possible to decide on the similarity between two given objects. Thus, depending on its value, the results returned by systems in a search may be satisfactory or not. However, the definition of similarity thresholds is difficult because it depends on several factors. Typically, specialists fix a threshold value for a given system, which is used in all searches. However, an expert-defined value is quite costly and not always possible. Therefore, this study proposes an approach for automatic and online estimation of the similarity threshold value, to be specifically used by content-based visual information retrieval system (image and video) search engines. The experimental results obtained with the proposed approach prove rather promising. For example, for one of the case studies, the performance of the proposed approach achieved 99.5 % efficiency in comparison with that obtained by a specialist using an empirical similarity threshold. Moreover, such automated approach becomes more scalable and less costly.Content-based retrieval systemsAutomatic and online setting of similarity thresholds in content-based visual information retrieval problems.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-8924http://www.repositorio.ufop.br/bitstream/123456789/7167/2/license.txt62604f8d955274beb56c80ce1ee5dcaeMD52ORIGINALARTIGO_AutomaticOnlineSetting.pdfARTIGO_AutomaticOnlineSetting.pdfapplication/pdf3085960http://www.repositorio.ufop.br/bitstream/123456789/7167/1/ARTIGO_AutomaticOnlineSetting.pdfceeeb5ce77b4c612564f909879530b89MD51123456789/71672018-04-23 13:45:02.423oai:localhost: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ório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332018-04-23T17:45:02Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.pt_BR.fl_str_mv |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
title |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
spellingShingle |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. Bessas, Izaquiel L. Content-based retrieval systems |
title_short |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
title_full |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
title_fullStr |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
title_full_unstemmed |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
title_sort |
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. |
author |
Bessas, Izaquiel L. |
author_facet |
Bessas, Izaquiel L. Pádua, Flávio Luis Cardeal Assis, Guilherme Tavares de Cardoso, Rodrigo T. N. Lacerda, Anisio Mendes |
author_role |
author |
author2 |
Pádua, Flávio Luis Cardeal Assis, Guilherme Tavares de Cardoso, Rodrigo T. N. Lacerda, Anisio Mendes |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Bessas, Izaquiel L. Pádua, Flávio Luis Cardeal Assis, Guilherme Tavares de Cardoso, Rodrigo T. N. Lacerda, Anisio Mendes |
dc.subject.por.fl_str_mv |
Content-based retrieval systems |
topic |
Content-based retrieval systems |
description |
Several information recovery systems use functions to determine similarity among objects in a collection. Such functions require a similarity threshold, from which it becomes possible to decide on the similarity between two given objects. Thus, depending on its value, the results returned by systems in a search may be satisfactory or not. However, the definition of similarity thresholds is difficult because it depends on several factors. Typically, specialists fix a threshold value for a given system, which is used in all searches. However, an expert-defined value is quite costly and not always possible. Therefore, this study proposes an approach for automatic and online estimation of the similarity threshold value, to be specifically used by content-based visual information retrieval system (image and video) search engines. The experimental results obtained with the proposed approach prove rather promising. For example, for one of the case studies, the performance of the proposed approach achieved 99.5 % efficiency in comparison with that obtained by a specialist using an empirical similarity threshold. Moreover, such automated approach becomes more scalable and less costly. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016 |
dc.date.accessioned.fl_str_mv |
2017-02-01T12:46:05Z |
dc.date.available.fl_str_mv |
2017-02-01T12:46:05Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
BESSAS, I. L. et al. Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. EURASIP Journal on Advances in Signal Processing, v. 2016, n. 32, p. 1-16, 2016. Disponível em: <http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16>. Acesso em: 20 jan. 2017. |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.ufop.br/handle/123456789/7167 |
dc.identifier.issn.none.fl_str_mv |
16876180 |
dc.identifier.uri2.pt_BR.fl_str_mv |
http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16 |
identifier_str_mv |
BESSAS, I. L. et al. Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. EURASIP Journal on Advances in Signal Processing, v. 2016, n. 32, p. 1-16, 2016. Disponível em: <http://download.springer.com/static/pdf/29/art%253A10.1186%252Fs13634-016-0324-4.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1186%2Fs13634-016-0324-4&token2=exp=1484910369~acl=%2Fstatic%2Fpdf%2F29%2Fart%25253A10.1186%25252Fs13634-016-0324-4.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1186%252Fs13634-016-0324-4*~hmac=095fb19f10096bbaa22ab30d86e5bc922726ab9dd235363e092133d48ce3df16>. Acesso em: 20 jan. 2017. 16876180 |
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