1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPBW4/35S5ML2 |
Repository | sid.inpe.br/sibgrapi@80/2009/08.17.17.33 |
Last Update | 2009:08.17.17.33.30 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi@80/2009/08.17.17.33.31 |
Metadata Last Update | 2022:06.14.00.13.58 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2009.40 |
Citation Key | SilvaSancConc:2009:AuDiPr |
Title | Automatic discrimination between printed and handwritten text in documents |
Format | Printed, On-line. |
Year | 2009 |
Access Date | 2024, May 05 |
Number of Files | 1 |
Size | 1199 KiB |
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2. Context | |
Author | 1 Silva, Lincoln Faria da 2 Sanchez, Angel 3 Conci, Aura |
Affiliation | 1 UFF 2 Universidad Rey Juan Carlos 3 UFF |
Editor | Nonato, Luis Gustavo Scharcanski, Jacob |
e-Mail Address | lincoln.faria@gmail.com |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI) |
Conference Location | Rio de Janeiro, RJ, Brazil |
Date | 11-14 Oct. 2009 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2010-08-28 20:03:26 :: lincoln.faria@gmail.com -> administrator :: 2022-06-14 00:13:58 :: administrator -> :: 2009 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | Data Mining document analysis text identification optical characters recognition Machine Vision |
Abstract | Recognition techniques for printed and handwritten text in scanned documents are significantly different. In this paper we address the problem of identifying each type. We can list at least four steps: digitalization, preprocessing, feature extraction and decision or classification. A new aspect of our approach is the use of data mining techniques on the decision step. A new set of features extracted of each word is proposed as well. Classification rules are mining and used to discern printed text from handwritten. The proposed system was tested in two public image databases. All possible measures of efficiency were computed achieving on every occasion quantities above 80%. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2009 > Automatic discrimination between... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Automatic discrimination between... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPBW4/35S5ML2 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPBW4/35S5ML2 |
Language | en |
Target File | 57993.pdf |
User Group | lincoln.faria@gmail.com |
Visibility | shown |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPEW34M/46SJQ2S 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2022/05.14.19.43 2 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy 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 |
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