Close

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/38737C8
Repositorysid.inpe.br/sibgrapi/2010/09.02.12.19
Last Update2010:09.02.12.19.13 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2010/09.02.12.19.13
Metadata Last Update2022:06.14.00.06.56 (UTC) administrator
DOI10.1109/SIBGRAPI.2010.55
Citation KeyAlvesHash:2010:TeReEx
TitleText Regions Extracted from Scene Images by Ultimate Attribute Opening and Decision Tree Classification
FormatPrinted, On-line.
Year2010
Access Date2024, Apr. 27
Number of Files1
Size1056 KiB
2. Context
Author1 Alves, Wonder Alexandre Luz
2 Hashimoto, Ronaldo Fumio
Affiliation1 Institute of Mathematics and Statistics - University of São Paulo
2 Institute of Mathematics and Statistics - University of São Paulo
EditorBellon, Olga
Esperança, Claudio
e-Mail Addresswonder@ime.usp.br
Conference NameConference on Graphics, Patterns and Images, 23 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
Date30 Aug.-3 Sep. 2010
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2010-10-01 04:19:38 :: wonder@ime.usp.br -> administrator :: 2010
2022-06-14 00:06:56 :: administrator -> :: 2010
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsscene-text localization
connected component approach
text information extraction
residual operator
AbstractIn this work we propose a method for localizing text regions within scene images consisting of two major stages. In the first stage, a set of potential text regions is extracted from the input image using residual operators (such as ultimate attribute opening and closing). In the second stage a set of features is obtained from each potential text region and this feature set will be later used as an input to a decision tree classifier in order to label these regions as text or non-text regions. Experiments performed using images from ICDAR public dataset show that this method is a good alternative for problems involving text location in scene images.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2010 > Text Regions Extracted...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Text Regions Extracted...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/38737C8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/38737C8
Languageen
Target Filepaper_final.pdf
User Groupwonder@ime.usp.br
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46SJT6B
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.20.21 5
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 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


Close