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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JRJTFE
Repositorysid.inpe.br/sibgrapi/2015/07.13.13.41
Last Update2015:08.13.20.26.56 (UTC) banon
Metadata Repositorysid.inpe.br/sibgrapi/2015/07.13.13.41.17
Metadata Last Update2022:05.18.22.20.58 (UTC) administrator
Citation KeyPessoaSchwSant:2015:ExCoFe
TitleAn experimental comparison of feature extraction and distance metrics for image retrieval
FormatOn-line
Year2015
Access Date2024, May 05
Number of Files1
Size183 KiB
2. Context
Author1 Pessoa, Ramon Figueiredo
2 Schwartz, William Robson
3 Santos, Jefersson Alex dos
Affiliation1 Universidade Federal de Minas Gerais (UFMG)
2 Universidade Federal de Minas Gerais (UFMG)
3 Universidade Federal de Minas Gerais (UFMG)
EditorRios, Ricardo Araujo
Paiva, Afonso
e-Mail Addressramon.pessoa@dcc.ufmg.br
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2015-07-13 13:41:17 :: ramon.pessoa@dcc.ufmg.br -> administrator ::
2015-08-13 20:24:25 :: administrator -> banon :: 2015
2015-08-13 20:26:56 :: banon -> administrator :: 2015
2022-05-18 22:20:58 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsCBIR experimental comparison
statistical analysis
feature extraction algorithms
distance metrics
AbstractThis paper seeks to do a comparative study of different features and distance metrics in order to analyze the impact of these factors in the process of Content-Based Image Retrieval (CBIR). One of the main contributions of this work was statistically analyze the impact of distance metrics in the process of image retrieval by content. We also observed statistically the impact of the variability among different classes and also the variability between images of the same image class. The results showed, for a sample collected, that the variation attributed to the class is approximately 99.85%. This confirms the fact that each algorithm will work best in a given situation. The comparative study showed the algorithms which had better accuracy rate to recover different image classes (in the dataset analysed) and also presented the reasons that possibly made these algorithms had better accuracy rate.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2015 > An experimental comparison...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JRJTFE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JRJTFE
Languageen
Target File20151208_ramon-pessoa_SIBGRAPI_WiP_2015_final.pdf
User Groupadministrator
banon
ramon.pessoa@dcc.ufmg.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 11
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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