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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/3U2CTAL
Repositorysid.inpe.br/sibgrapi/2019/09.08.11.36
Last Update2019:09.08.11.36.49 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2019/09.08.11.36.49
Metadata Last Update2022:06.14.00.09.30 (UTC) administrator
DOI10.1109/SIBGRAPI.2019.00037
Citation KeyLourençoSilvFern:2019:LeApTr
TitleHierarchy-of-Visual-Words: a Learning-based Approach for Trademark Image Retrieval
FormatOn-line
Year2019
Access Date2024, Apr. 28
Number of Files1
Size740 KiB
2. Context
Author1 Lourenço, Vítor N.
2 Silva, Gabriela G.
3 Fernandes, Leandro A. F.
Affiliation1 Universidade Federal Fluminense
2 Universidade Federal Fluminense
3 Universidade Federal Fluminense
EditorOliveira, Luciano Rebouças de
Sarder, Pinaki
Lage, Marcos
Sadlo, Filip
e-Mail Addressvitorlourenco@id.uff.br
Conference NameConference on Graphics, Patterns and Images, 32 (SIBGRAPI)
Conference LocationRio de Janeiro, RJ, Brazil
Date28-31 Oct. 2019
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2019-09-08 11:36:49 :: vitorlourenco@id.uff.br -> administrator ::
2022-06-14 00:09:30 :: administrator -> vitorlourenco@id.uff.br :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsTrademark image retrieval
visual feature extraction and matching
learning-based approach
AbstractIn this paper, we present the Hierarchy-of-Visual-Words (HoVW), a novel trademark image retrieval (TIR) method that decomposes images into simpler geometric shapes and defines a descriptor for binary trademark image representation by encoding the hierarchical arrangement of component shapes. The proposed hierarchical organization of visual data stores each component shape as a visual word. It is capable of representing the geometry of individual elements and the topology of the trademark image, making the descriptor robust against linear as well as to some level of nonlinear transformation. Experiments show that HoVW outperforms previous TIR methods on the MPEG-7 CE-1 and MPEG-7 CE-2 image databases.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Hierarchy-of-Visual-Words: a Learning-based...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/3U2CTAL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/3U2CTAL
Languageen
Target File35-cr.pdf
User Groupvitorlourenco@id.uff.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/3UA4FNL
8JMKD3MGPEW34M/3UA4FPS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2019/10.25.18.30.33 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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 volume
7. Description control
e-Mail (login)vitorlourenco@id.uff.br
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