Close

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/w4Tnu
Repositorysid.inpe.br/banon/2002/11.05.12.14
Last Update2002:11.04.02.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2002/11.05.12.14.52
Metadata Last Update2022:06.14.00.12.06 (UTC) administrator
DOI10.1109/SIBGRA.2000.883903
Citation KeyMoritaLetYacBorSab:2000:ReHaDa
TitleRecognition of handwritten dates on bank checks using an HMM approach
Year2000
Access Date2024, May 04
Number of Files1
Size487 KiB
2. Context
Author1 Morita, Marisa Emika
2 Lethelier, Edouard
3 Yacoubi, Abdenaim El
4 Bortolozzi, Flávio
5 Sabourin, Robert
EditorCarvalho, Paulo Cezar Pinto
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
Date17-20 Oct. 2000
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Pages113-120
Book TitleProceedings
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History (UTC)2008-07-17 14:10:50 :: administrator -> banon ::
2008-08-26 15:23:01 :: banon -> administrator ::
2009-08-13 20:36:54 :: administrator -> banon ::
2010-08-28 20:00:09 :: banon -> administrator ::
2022-06-14 00:12:06 :: administrator -> :: 2000
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordshandwriting recognition
automatic handwritten date recognition
Brazilian bank checks
omni-writer context
fixed lexicon
explicit segmentation technique
grapheme sequence
hidden Markov models
small database images
AbstractThe article presents the first results of our system applied to the automatic recognition of handwritten dates on Brazilian bank checks. Considering the omni-writer context, we detail our recognition module dedicated to processing the month field. This module is based on the combination of holistic and analytical approaches with a fixed lexicon. Both approaches operate with a single explicit segmentation technique to provide a grapheme sequence for the purposed hidden Markov models of each recognizer. We show significant improvements when combining both modules to get a satisfactory recognition rate considering the small database images we work with. Finally, we present various perspectives for future work.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2000 > Recognition of handwritten...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Recognition of handwritten...
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/6qtX3pFwXQZeBBx/w4Tnu
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/w4Tnu
Target File113-120.pdf
User Groupadministrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46PN6AP
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/04.27.03.08 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
NotesThe conference was held in Gramado, RS, Brazil, from October 17 to 20.
Empty Fieldsaffiliation archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition electronicmailaddress format group isbn issn label language lineage mark mirrorrepository nextedition numberofvolumes orcid 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