Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PFR8PP
Repositorysid.inpe.br/sibgrapi/2017/08.21.20.59
Last Update2017:08.21.20.59.40 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.21.20.59.40
Metadata Last Update2022:06.14.00.08.56 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.39
Citation KeyBalreiraWalt:2017:HaSyPu
TitleHandwriting Synthesis from Public Fonts
FormatOn-line
Year2017
Access Date2024, May 02
Number of Files1
Size3849 KiB
2. Context
Author1 Balreira, Dennis Giovani
2 Walter, Marcelo
Affiliation1 Institute of Informatics - Universidade Federal do Rio Grande do Sul
2 Institute of Informatics - Universidade Federal do Rio Grande do Sul
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addressdgbalreira@inf.ufrgs.br
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-21 20:59:40 :: dgbalreira@inf.ufrgs.br -> administrator ::
2022-06-14 00:08:56 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordshandwriting synthesis
public fonts
AbstractHandwriting synthesis generates renderings of text which look like they were written by a human but are in fact synthesized by a model. From an input sample of the desired handwriting, we introduce an algorithm that finds the best match between characters using as source for the output text the large collection of publicly available fonts designed to look like handwriting. For each character in the desired output text, we find the best match among the public fonts using a metric that matches both the shape and appearance of the input real character. Once we have the set of best characters we build the output sentence or paragraph by concatenation of individual characters. Our results show that even though human calligraphy is highly individual and specialized, visually similar renderings are possible for many applications that do not demand full similarity. On a user study with 12 subjects, our synthesis results were considered, on average, 71% similar to the input samples.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Handwriting Synthesis from...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Handwriting Synthesis from...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 21/08/2017 17:59 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PFR8PP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PFR8PP
Languageen
Target FilePID4960255.pdf
User Groupdgbalreira@inf.ufrgs.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 6
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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


Close