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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3C8EHNS
Repositorysid.inpe.br/sibgrapi/2012/07.06.13.25
Last Update2012:07.06.13.25.27 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2012/07.06.13.25.27
Metadata Last Update2022:06.14.00.07.24 (UTC) administrator
DOI10.1109/SIBGRAPI.2012.15
Citation KeyCostaHumpTrai:2012:EfAlFr
TitleAn Efficient Algorithm for Fractal Analysis of Textures
FormatDVD, On-line.
Year2012
Access Date2024, Apr. 27
Number of Files1
Size2310 KiB
2. Context
Author1 Costa, Alceu Ferraz
2 Humpire-Mamani, Gabriel
3 Traina, Agma Juci Machado
Affiliation1 University of São Paulo, USP, Department of Computer Science 
2 University of São Paulo, USP, Department of Computer Science 
3 University of São Paulo, USP, Department of Computer Science
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressalceufc@icmc.usp.br
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 :: alceufc@icmc.usp.br -> administrator :: 2012
2022-03-08 21:03:22 :: administrator -> menottid@gmail.com :: 2012
2022-03-10 12:50:55 :: menottid@gmail.com -> administrator :: 2012
2022-06-14 00:07:24 :: administrator -> :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsFractal analysis
texture
feature extraction
content based image retrieval
image classification
image processing
AbstractIn this paper we propose a new and efficient texture feature extraction method: the Segmentation-based Fractal Texture Analysis, or SFTA. The extraction algorithm consists in decomposing the input image into a set of binary images from which the fractal dimensions of the resulting regions are computed in order to describe segmented texture patterns. The decomposition of the input image is achieved by the Two-Threshold Binary Decomposition (TTBD) algorithm, which we also propose in this work. We evaluated SFTA for the tasks of content-based image retrieval (CBIR) and image classification, comparing its performance to that of other widely employed feature extraction methods such as Haralick and Gabor filter banks. SFTA achieved higher precision and accuracy for CBIR and image classification. Additionally, SFTA was at least 3.7 times faster than Gabor and 1.6 times faster than Haralick with respect to feature extraction time.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2012 > An Efficient Algorithm...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > An Efficient Algorithm...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3C8EHNS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C8EHNS
Languageen
Target FilePID2438001.pdf
User Groupalceufc@icmc.usp.br
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 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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