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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3C9K7LE
Repositorysid.inpe.br/sibgrapi/2012/07.13.18.20
Last Update2012:07.13.18.20.02 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2012/07.13.18.20.02
Metadata Last Update2022:06.14.00.07.32 (UTC) administrator
DOI10.1109/SIBGRAPI.2012.21
Citation KeyVieiraChieFerrGonz:2012:ImMiAn
TitleImage micro-pattern analysis using Fuzzy Numbers
FormatDVD, On-line.
Year2012
Access Date2025, July 02
Number of Files1
Size828 KiB
2. Context
Author1 Vieira, Raissa Tavares
2 Chierici, Carlos Eduardo de Oliveira
3 Ferraz, Carolina Toledo
4 Gonzaga, Adilson
Affiliation1 University of São Paulo
2 University of São Paulo
3 University of São Paulo
4 University of São Paulo
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addresscaroltoledoferraz@gmail.com
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto, MG, Brazil
Date22-25 Aug. 2012
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2012-09-20 16:45:34 :: caroltoledoferraz@gmail.com -> administrator :: 2012
2022-03-08 21:03:24 :: administrator -> menottid@gmail.com :: 2012
2022-03-10 13:05:09 :: menottid@gmail.com -> administrator :: 2012
2022-06-14 00:07:32 :: administrator -> :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsmicro-pattern analysis
fuzzy numbers
texture analysis
AbstractThis paper proposes a new methodology for micropattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial context of the image, such as edge, line, spot, blob, corner, texture, and more complex patterns. By treating a pixel neighborhood as a fuzzy set and each pixel gray-level as a fuzzy number, we can evaluate the membership degree of the central pixel to the others. We have called this method the Local Fuzzy Pattern (LFP). Using a sigmoid membership function, we proved that the proposed methodology surpasses the Hit-rate of the Local Binary Pattern (LBP), for texture classification. The LFP proved to be robust to image rotation. Moreover, our proposed formulation for the LFP is a generalization of previously published techniques, such as Texture Unit, LBP, FUNED, and Census Transform.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2012 > Image micro-pattern analysis...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Image micro-pattern analysis...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3C9K7LE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C9K7LE
Languageen
Target FileImage micro-pattern analysis using Fuzzy Numbers.pdf
User Groupcaroltoledoferraz@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SL8GS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.03.31 33
sid.inpe.br/sibgrapi/2022/06.10.21.49 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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


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