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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3S4NEGH
Repositorysid.inpe.br/sibgrapi/2018/10.25.19.19
Last Update2018:10.25.19.19.49 (UTC) pavmbr@gmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2018/10.25.19.19.49
Metadata Last Update2022:05.18.22.18.35 (UTC) administrator
Citation KeyFreitasMira:2018:NeShDe
TitleNew Shape Descriptors based on Tensor Scale with Global Features
FormatOn-line
Year2018
Access Date2024, May 02
Number of Files1
Size2425 KiB
2. Context
Author1 Freitas, Anderson M.
2 Miranda, Paulo A. V.
Affiliation1 Institute of Mathematics and Statistics, University of São Paulo
2 Institute of Mathematics and Statistics, University of São Paulo
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addresspavmbr@gmail.com
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2018-10-25 19:19:49 :: pavmbr@gmail.com -> administrator ::
2022-05-18 22:18:35 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsTensor Scale
Shape Descriptors
Content-Based Image Retrieval
AbstractIn this work, two new shape descriptors are proposed for tasks in Content-Based Image Retrieval (CBIR) and Shape Analysis, which are built upon an extended tensor scale based on the Euclidean Distance Transform (EDT). First, the tensor scale algorithm is applied to extract shape attributes from its local structures as represented by the largest ellipse within a homogeneous region centered at each image pixel. In the new descriptors, the upper limit of the interval of local orientation of tensor scale ellipses is extended from π to 2π, to discriminate the description of local structures better. Then, the new descriptors are built based on different sampling approaches, aiming to summarize the most relevant features. Experimental results for different shape datasets (MPEG-7 and MNIST) are presented to illustrate and validate the methods. TSS can achieve high retrieval values comparable to state-of-the-art methods, which usually rely on time-consuming correspondence optimization algorithms, but uses a more straightforward and faster distance function, while the even faster linear complexity of TSB leads to a suitable solution for huge shape collections.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2018 > New Shape Descriptors...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3S4NEGH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3S4NEGH
Languageen
Target Filetss-tsb-descriptors-sibgrapi-wtd-2018 (1).pdf
User Grouppavmbr@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 12
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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