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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M9L6JB
Repositorysid.inpe.br/sibgrapi/2016/08.16.15.51
Last Update2016:08.16.15.51.15 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/08.16.15.51.15
Metadata Last Update2022:05.18.22.21.08 (UTC) administrator
Citation KeySousaeSantosPedr:2016:ImHuSk
TitleImprovements on human skin segmentation in digital images
FormatOn-line
Year2016
Access Date2024, May 03
Number of Files1
Size1387 KiB
2. Context
Author1 Sousa e Santos, Anderson Carlos
2 Pedrini, Hélio
Affiliation1 University of Campinas
2 University of Campinas
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressmr.acarlos@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2016-08-16 15:51:15 :: mr.acarlos@gmail.com -> administrator ::
2022-05-18 22:21:08 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordssegmentation
saliency
texture
skin detection
AbstractHuman skin segmentation has several applications in computer vision and pattern recognition fields, whose main purpose is to distinguish skin and non-skin regions. Despite the large number of available methods, accurate skin segmentation is still a challenging task. Three main contributions toward this need are presented in this work. The first is a self-contained method for adaptive skin segmentation that adjusts the color model to a particular image. The second is the combination of saliency detection with color skin segmentation, which performs a background removal to eliminate non-skin regions. The third is a texture-based improvement imployed to characterize non-skin regions and thus eliminates color ambiguity adding a second vote. Experimental results on public data sets demonstrate a significant improvement of the proposed methods for human skin segmentation over state-of-the-art approaches.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > Improvements on human...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M9L6JB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M9L6JB
Languageen
Target Filepaper.pdf
User Groupmr.acarlos@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 5
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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