1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 6qtX3pFwXQZG2LgkFdY/MfxFy |
Repository | sid.inpe.br/sibgrapi@80/2006/08.24.16.48 |
Last Update | 2006:08.24.16.48.48 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi@80/2006/08.24.16.48.49 |
Metadata Last Update | 2022:06.14.00.13.24 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2006.26 |
Citation Key | Cuadros-VargasGerCasBatNon:2006:Im2DMe |
Title | Improving 2D mesh image segmentation with Markovian Random Fields  |
Format | On-line |
Year | 2006 |
Access Date | 2025, Feb. 10 |
Number of Files | 1 |
Size | 2118 KiB |
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2. Context | |
Author | 1 Cuadros-Vargas, Alex J. 2 Gerhardinger, Leandro C. 3 Castro, Mário 4 Batista Neto, João 5 Nonato, Luis G. |
Affiliation | 1 ICMC - Instituto de Ciências Matemáticas e de Computação - USP 2 ICMC - Instituto de Ciências Matemáticas e de Computação - USP 3 ICMC - Instituto de Ciências Matemáticas e de Computaão - USP 4 ICMC - Instituto de Ciências Matemáticas e de Computaão - USP 5 ICMC - Instituto de Ciências Matemáticas e de Computaão - USP |
Editor | Oliveira Neto, Manuel Menezes de Carceroni, Rodrigo Lima |
e-Mail Address | jbatista@icmc.usp.br |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI) |
Conference Location | Manaus, AM, Brazil |
Date | 8-11 Oct. 2006 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2006-08-24 16:48:49 :: jdesbn -> banon :: 2006-08-30 21:49:34 :: banon -> jdesbn :: 2008-07-17 14:11:04 :: jdesbn -> administrator :: 2009-08-13 20:38:15 :: administrator -> banon :: 2010-08-28 20:02:25 :: banon -> administrator :: 2022-06-14 00:13:24 :: administrator -> :: 2006 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | Polygonal Meshes Texture Analysis Segmentation |
Abstract | Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterparts, such as Imesh \cite{Vargas:05} perform the task by following a set of well defined rules derived from the geometry of the triangles, but with no statistical information of the mesh elements. This paper presents a novel segmentation method that combines the original Imesh image-based segmentation approach with Markovian Random Field (MRF) models. It takes an image as input, generate a mesh of triangles and, by treating the mesh as a Markovian field, produces quality unsupervised segmentation. The results have demonstrated that the method not only provides better segmentation than that of original Imesh, but is also capable of producing MRF-like segmentation output for certain types of images, with considerable cut in processing times. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2006 > Improving 2D mesh... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Improving 2D mesh... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/MfxFy |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/MfxFy |
Language | en |
Target File | Vargas-MRF_Mesh.pdf |
User Group | jdesbn administrator |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46RFT7E 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/05.08.00.20 14 sid.inpe.br/sibgrapi/2022/06.10.21.49 5 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository 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 |
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