Recovery of temporal information from static images of handwriting
Identifieur interne : 000885 ( Istex/Corpus ); précédent : 000884; suivant : 000886Recovery of temporal information from static images of handwriting
Auteurs : S. Doermann ; Azriel RosenfeldSource :
- International Journal of Computer Vision [ 0920-5691 ] ; 1995-06-01.
Abstract
Abstract: The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered. We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image. We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information. We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.
Url:
DOI: 10.1007/BF01450853
Links to Exploration step
ISTEX:C1B04C00CC4642C16E5DBD5475B80960837B2BF4Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Recovery of temporal information from static images of handwriting</title><author><name sortKey="Doermann, S" sort="Doermann, S" uniqKey="Doermann S" first="S." last="Doermann">S. Doermann</name><affiliation><mods:affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</mods:affiliation></affiliation></author><author><name sortKey="Rosenfeld, Azriel" sort="Rosenfeld, Azriel" uniqKey="Rosenfeld A" first="Azriel" last="Rosenfeld">Azriel Rosenfeld</name><affiliation><mods:affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:C1B04C00CC4642C16E5DBD5475B80960837B2BF4</idno><date when="1995" year="1995">1995</date><idno type="doi">10.1007/BF01450853</idno><idno type="url">https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000885</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Recovery of temporal information from static images of handwriting</title><author><name sortKey="Doermann, S" sort="Doermann, S" uniqKey="Doermann S" first="S." last="Doermann">S. Doermann</name><affiliation><mods:affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</mods:affiliation></affiliation></author><author><name sortKey="Rosenfeld, Azriel" sort="Rosenfeld, Azriel" uniqKey="Rosenfeld A" first="Azriel" last="Rosenfeld">Azriel Rosenfeld</name><affiliation><mods:affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">International Journal of Computer Vision</title><title level="j" type="abbrev">Int J Comput Vision</title><idno type="ISSN">0920-5691</idno><idno type="eISSN">1573-1405</idno><imprint><publisher>Kluwer Academic Publishers</publisher><pubPlace>Dordrecht</pubPlace><date type="published" when="1995-06-01">1995-06-01</date><biblScope unit="volume">15</biblScope><biblScope unit="issue">1-2</biblScope><biblScope unit="page" from="143">143</biblScope><biblScope unit="page" to="164">164</biblScope></imprint><idno type="ISSN">0920-5691</idno></series><idno type="istex">C1B04C00CC4642C16E5DBD5475B80960837B2BF4</idno><idno type="DOI">10.1007/BF01450853</idno><idno type="ArticleID">BF01450853</idno><idno type="ArticleID">Art7</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0920-5691</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered. We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image. We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information. We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>David S. Doermann</name><affiliations><json:string>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</json:string></affiliations></json:item><json:item><name>Azriel Rosenfeld</name><affiliations><json:string>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</json:string></affiliations></json:item></author><articleId><json:string>BF01450853</json:string><json:string>Art7</json:string></articleId><language><json:string>eng</json:string></language><abstract>Abstract: The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered. We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image. We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information. We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.</abstract><qualityIndicators><score>7.496</score><pdfVersion>1.3</pdfVersion><pdfPageSize>555 x 738 pts</pdfPageSize><refBibsNative>false</refBibsNative><keywordCount>0</keywordCount><abstractCharCount>1393</abstractCharCount><pdfWordCount>8712</pdfWordCount><pdfCharCount>54770</pdfCharCount><pdfPageCount>22</pdfPageCount><abstractWordCount>208</abstractWordCount></qualityIndicators><title>Recovery of temporal information from static images of handwriting</title><genre.original><json:string>OriginalPaper</json:string></genre.original><genre><json:string>research-article</json:string></genre><host><issue>1-2</issue><subject><json:item><value>Artificial Intelligence (incl. Robotics)</value></json:item><json:item><value>Computer Imaging, Graphics and Computer Vision</value></json:item><json:item><value>Image Processing</value></json:item><json:item><value>Automation and Robotics</value></json:item></subject><journalId><json:string>11263</json:string></journalId><language><json:string>unknown</json:string></language><eissn><json:string>1573-1405</json:string></eissn><title>International Journal of Computer Vision</title><genre.original><json:string>Archive Journal</json:string></genre.original><volume>15</volume><pages><last>164</last><first>143</first></pages><issn><json:string>0920-5691</json:string></issn><genre><json:string>Journal</json:string></genre><publicationDate>1995</publicationDate><copyrightDate>1995</copyrightDate></host><publicationDate>1995</publicationDate><copyrightDate>1995</copyrightDate><doi><json:string>10.1007/BF01450853</json:string></doi><id>C1B04C00CC4642C16E5DBD5475B80960837B2BF4</id><fulltext><json:item><original>true</original><mimetype>application/pdf</mimetype><extension>pdf</extension><uri>https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/fulltext/pdf</uri></json:item><json:item><original>false</original><mimetype>application/zip</mimetype><extension>zip</extension><uri>https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">Recovery of temporal information from static images of handwriting</title><respStmt xml:id="ISTEX-API" resp="Références bibliographiques récupérées via GROBID" name="ISTEX-API (INIST-CNRS)"></respStmt></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Kluwer Academic Publishers</publisher><pubPlace>Dordrecht</pubPlace><availability><p>SPRINGER</p></availability><date>1992-11-15</date></publicationStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Recovery of temporal information from static images of handwriting</title><author><persName><forename type="first">David</forename><surname>Doermann</surname></persName><affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</affiliation></author><author><persName><forename type="first">Azriel</forename><surname>Rosenfeld</surname></persName><affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</affiliation></author></analytic><monogr><title level="j">International Journal of Computer Vision</title><title level="j" type="abbrev">Int J Comput Vision</title><idno type="JournalID">11263</idno><idno type="pISSN">0920-5691</idno><idno type="eISSN">1573-1405</idno><idno type="IssueArticleCount">7</idno><idno type="VolumeIssueCount">3</idno><imprint><publisher>Kluwer Academic Publishers</publisher><pubPlace>Dordrecht</pubPlace><date type="published" when="1995-06-01"></date><biblScope unit="volume">15</biblScope><biblScope unit="issue">1-2</biblScope><biblScope unit="page" from="143">143</biblScope><biblScope unit="page" to="164">164</biblScope></imprint></monogr><idno type="istex">C1B04C00CC4642C16E5DBD5475B80960837B2BF4</idno><idno type="DOI">10.1007/BF01450853</idno><idno type="ArticleID">BF01450853</idno><idno type="ArticleID">Art7</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1992-11-15</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Abstract: The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered. We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image. We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information. We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.</p></abstract><textClass><keywords scheme="Journal Subject"><list><head>Computer Science</head><item><term>Artificial Intelligence (incl. Robotics)</term></item><item><term>Computer Imaging, Graphics and Computer Vision</term></item><item><term>Image Processing</term></item><item><term>Automation and Robotics</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1992-11-15">Created</change><change when="1995-06-01">Published</change><change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-3-19">References added</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><original>false</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Springer, Publisher found" wicri:toSee="no header"><istex:xmlDeclaration>version="1.0" encoding="UTF-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//Springer-Verlag//DTD A++ V2.4//EN" URI="http://devel.springer.de/A++/V2.4/DTD/A++V2.4.dtd" name="istex:docType"></istex:docType><istex:document><Publisher><PublisherInfo><PublisherName>Kluwer Academic Publishers</PublisherName><PublisherLocation>Dordrecht</PublisherLocation></PublisherInfo><Journal><JournalInfo JournalProductType="ArchiveJournal" NumberingStyle="Unnumbered"><JournalID>11263</JournalID><JournalPrintISSN>0920-5691</JournalPrintISSN><JournalElectronicISSN>1573-1405</JournalElectronicISSN><JournalTitle>International Journal of Computer Vision</JournalTitle><JournalAbbreviatedTitle>Int J Comput Vision</JournalAbbreviatedTitle><JournalSubjectGroup><JournalSubject Type="Primary">Computer Science</JournalSubject><JournalSubject Type="Secondary">Artificial Intelligence (incl. Robotics)</JournalSubject><JournalSubject Type="Secondary">Computer Imaging, Graphics and Computer Vision</JournalSubject><JournalSubject Type="Secondary">Image Processing</JournalSubject><JournalSubject Type="Secondary">Automation and Robotics</JournalSubject></JournalSubjectGroup></JournalInfo><Volume><VolumeInfo VolumeType="Regular" TocLevels="0"><VolumeIDStart>15</VolumeIDStart><VolumeIDEnd>15</VolumeIDEnd><VolumeIssueCount>3</VolumeIssueCount></VolumeInfo><Issue IssueType="Combined"><IssueInfo TocLevels="0"><IssueIDStart>1</IssueIDStart><IssueIDEnd>2</IssueIDEnd><IssueArticleCount>7</IssueArticleCount><IssueHistory><CoverDate><Year>1995</Year><Month>6</Month></CoverDate></IssueHistory><IssueCopyright><CopyrightHolderName>Kluwer Academic Publishers</CopyrightHolderName><CopyrightYear>1995</CopyrightYear></IssueCopyright></IssueInfo><Article ID="Art7"><ArticleInfo Language="En" ArticleType="OriginalPaper" NumberingStyle="Unnumbered" TocLevels="0" ContainsESM="No"><ArticleID>BF01450853</ArticleID><ArticleDOI>10.1007/BF01450853</ArticleDOI><ArticleSequenceNumber>7</ArticleSequenceNumber><ArticleTitle Language="En">Recovery of temporal information from static images of handwriting</ArticleTitle><ArticleFirstPage>143</ArticleFirstPage><ArticleLastPage>164</ArticleLastPage><ArticleHistory><RegistrationDate><Year>2005</Year><Month>3</Month><Day>27</Day></RegistrationDate><Received><Year>1992</Year><Month>11</Month><Day>15</Day></Received><Revised><Year>1993</Year><Month>3</Month><Day>15</Day></Revised></ArticleHistory><ArticleCopyright><CopyrightHolderName>Kluwer Academic Publishers</CopyrightHolderName><CopyrightYear>1995</CopyrightYear></ArticleCopyright><ArticleGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ArticleGrants><ArticleContext><JournalID>11263</JournalID><VolumeIDStart>15</VolumeIDStart><VolumeIDEnd>15</VolumeIDEnd><IssueIDStart>1</IssueIDStart><IssueIDEnd>2</IssueIDEnd></ArticleContext></ArticleInfo><ArticleHeader><AuthorGroup><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>David</GivenName><GivenName>S.</GivenName><FamilyName>Doermann</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Azriel</GivenName><FamilyName>Rosenfeld</FamilyName></AuthorName></Author><Affiliation ID="Aff1"><OrgDivision>Document Processing Group, Center for Automation Research</OrgDivision><OrgName>University of Maryland</OrgName><OrgAddress><Postcode>20742-3411</Postcode><City>College Park</City><State>MD</State></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered.</Para><Para>We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image.</Para><Para>We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information.</Para><Para>We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.</Para></Abstract><ArticleNote Type="Misc"><SimplePara>The support of this research by the Ricoh Corporation is gratefully acknowledged.</SimplePara></ArticleNote></ArticleHeader><NoBody></NoBody></Article></Issue></Volume></Journal></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Recovery of temporal information from static images of handwriting</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Recovery of temporal information from static images of handwriting</title></titleInfo><name type="personal"><namePart type="given">David</namePart><namePart type="given">S.</namePart><namePart type="family">Doermann</namePart><affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Azriel</namePart><namePart type="family">Rosenfeld</namePart><affiliation>Document Processing Group, Center for Automation Research, University of Maryland, 20742-3411, College Park, MD</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="OriginalPaper"></genre><originInfo><publisher>Kluwer Academic Publishers</publisher><place><placeTerm type="text">Dordrecht</placeTerm></place><dateCreated encoding="w3cdtf">1992-11-15</dateCreated><dateIssued encoding="w3cdtf">1995-06-01</dateIssued><copyrightDate encoding="w3cdtf">1995</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: The problem of off-line handwritten character recognition has eluded a satisfactory solution for several decades. Researchers working in the area of on-line recognition have had greater success, but the possibility of extracting on-line information from static images has not been fully explored. The experience of forensic document examiners assures us that in many cases, such information can be successfully recovered. We outline the design of a system for the recovery of temporal information from static handwritten images. We provide a taxonomy of local, regional and global temporal clues which are often found in hand-written samples, and describe methods for recovering these clues from the image. We show how this system can benefit from obtaining a comprehensive understanding of the handwriting signal and a detailed analysis of stroke and sub-stroke properties. We suggest that the recovery task requires that we break away from traditional thresholding and thinning techniques, and we provide a framework for such analysis. We demonstrate how isolated temporal clues can reliably be extracted from this framework and propose a control structure for integrating the partial information. We show how many seemingly ambiguous situations can be resolved by the derived clues and our knowledge of the writing process, and provide several examples to illustrate our approach.</abstract><relatedItem type="host"><titleInfo><title>International Journal of Computer Vision</title></titleInfo><titleInfo type="abbreviated"><title>Int J Comput Vision</title></titleInfo><genre type="Journal" displayLabel="Archive Journal"></genre><originInfo><dateIssued encoding="w3cdtf">1995-06-01</dateIssued><copyrightDate encoding="w3cdtf">1995</copyrightDate></originInfo><subject><genre>Computer Science</genre><topic>Artificial Intelligence (incl. Robotics)</topic><topic>Computer Imaging, Graphics and Computer Vision</topic><topic>Image Processing</topic><topic>Automation and Robotics</topic></subject><identifier type="ISSN">0920-5691</identifier><identifier type="eISSN">1573-1405</identifier><identifier type="JournalID">11263</identifier><identifier type="IssueArticleCount">7</identifier><identifier type="VolumeIssueCount">3</identifier><part><date>1995</date><detail type="volume"><number>15</number><caption>vol.</caption></detail><detail type="issue"><number>1-2</number><caption>no.</caption></detail><extent unit="pages"><start>143</start><end>164</end></extent></part><recordInfo><recordOrigin>Kluwer Academic Publishers, 1995</recordOrigin></recordInfo></relatedItem><identifier type="istex">C1B04C00CC4642C16E5DBD5475B80960837B2BF4</identifier><identifier type="DOI">10.1007/BF01450853</identifier><identifier type="ArticleID">BF01450853</identifier><identifier type="ArticleID">Art7</identifier><accessCondition type="use and reproduction" contentType="copyright">Kluwer Academic Publishers, 1995</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Kluwer Academic Publishers, 1995</recordOrigin></recordInfo></mods></metadata><enrichments><istex:refBibTEI uri="https://api.istex.fr/document/C1B04C00CC4642C16E5DBD5475B80960837B2BF4/enrichments/refBib"><teiHeader></teiHeader><text><front></front><body></body><back><listBibl><biblStruct xml:id="b0"><analytic><title level="a" type="main">The interpretation and recognition of interfering strokes</title><author><persName><forename type="first">D</forename><surname>Doermann</surname></persName></author><author><persName><forename type="first">A</forename><surname>Rosenfeld</surname></persName></author></analytic><monogr><title level="m">Proceedings of the International Work.~hop on b)-ontiers in Handwriting Recognition</title><meeting>the International Work.~hop on b)-ontiers in Handwriting Recognition</meeting><imprint><date type="published" when="1993"></date><biblScope unit="page" from="41" to="50"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b1"><monogr><title level="m" type="main">Document Image Understanding: Integrating Recovery andlnterpretation</title><author><persName><forename type="first">D</forename><forename type="middle">S</forename><surname>Doermann</surname></persName></author><imprint><date type="published" when="1993"></date><pubPlace>College Park</pubPlace></imprint></monogr></biblStruct><biblStruct xml:id="b2"><analytic><title level="a" type="main">Mailpiece preprocessing: The population of character parts</title><author><persName><forename type="first">D</forename><forename type="middle">S</forename><surname>Doermann</surname></persName></author><author><persName><forename type="first">A</forename><surname>Rosenfeld</surname></persName></author></analytic><monogr><title level="m">Proceedings of the USPS Advanced Technology Conference</title><meeting>the USPS Advanced Technology Conference</meeting><imprint><date type="published" when="1990"></date><biblScope unit="page" from="961" to="972"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b3"><analytic><title level="a" type="main">Instrument grasp: A model and its effects on handwritten strokes</title><author><persName><forename type="first">D</forename><forename type="middle">S</forename><surname>Doermann</surname></persName></author><author><persName><forename type="first">V</forename><surname>Varma</surname></persName></author></analytic><monogr><title level="j">Pattern Recognition</title><imprint><biblScope unit="volume">27</biblScope><biblScope unit="issue">2</biblScope><biblScope unit="page" from="233" to="245"></biblScope><date type="published" when="1994"></date></imprint></monogr></biblStruct><biblStruct xml:id="b4"><analytic><title level="a" type="main">Representing the dynamics of a static form</title><author><persName><forename type="first">J</forename><forename type="middle">J</forename><surname>Freyd</surname></persName></author></analytic><monogr><title level="j">Memory and Cognition</title><imprint><biblScope unit="volume">4</biblScope><biblScope unit="page" from="342" to="346"></biblScope><date type="published" when="1983"></date></imprint></monogr></biblStruct><biblStruct xml:id="b5"><analytic><title level="a" type="main">Recognition of handprinted characters by nonlinear elastic matching</title><author><persName><forename type="first">Y</forename><surname>Fujimoto</surname></persName></author><author><persName><forename type="first">S</forename><surname>Kadota</surname></persName></author><author><persName><forename type="first">S</forename><surname>Hayashi</surname></persName></author><author><persName><forename type="first">M</forename><surname>Yakarnoto</surname></persName></author><author><persName><forename type="first">S</forename><surname>Yajima</surname></persName></author><author><persName><forename type="first">M</forename><surname>Yasuda</surname></persName></author></analytic><monogr><title level="m">Proceedings of the International Conference on Pattern Recognition</title><meeting>the International Conference on Pattern Recognition</meeting><imprint><date type="published" when="1976"></date><biblScope unit="page" from="113" to="1"></biblScope></imprint></monogr><note>t. 8</note></biblStruct><biblStruct xml:id="b6"><analytic><title level="a" type="main">Separating handwritten text from interfering strokes</title><author><persName><forename type="first">V</forename><surname>Govindaraju</surname></persName></author><author><persName><forename type="first">S</forename><forename type="middle">N</forename><surname>Srihari</surname></persName></author></analytic><monogr><title level="m">From Pixels to Features</title><imprint><publisher>North Holland</publisher><date type="published" when="1992"></date><biblScope unit="page" from="17" to="28"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b7"><monogr><title level="m" type="main">Special Issue: Document Analysis Techniques. Machine Vision and Applications</title><author><persName><forename type="first">R</forename><surname>Kasturi</surname></persName></author><author><persName><forename type="first">O</forename><surname>Gorman</surname></persName></author><author><persName><forename type="first">L</forename></persName></author><imprint><date type="published" when="1992"></date><biblScope unit="page" from="141" to="247"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b8"><analytic><title level="a" type="main">Experiments in online script recognition</title><author><persName><forename type="first">E</forename><surname>Mandler</surname></persName></author><author><persName><forename type="first">R</forename><surname>Oed</surname></persName></author><author><persName><forename type="first">W</forename><surname>Doster</surname></persName></author></analytic><monogr><title level="m">Image Analysis: Proceedings of the 4th Scandinavian Con.fkrence</title><imprint><date type="published" when="1985"></date><biblScope unit="page" from="77" to="86"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b9"><analytic><title level="a" type="main">Thin line representation from contour representation of handprinted characters</title><author><persName><forename type="first">H</forename><surname>Nishida</surname></persName></author><author><persName><forename type="first">T</forename><surname>Suzuki</surname></persName></author><author><persName><forename type="first">S</forename><surname>Mori</surname></persName></author></analytic><monogr><title level="m">From Pixels to Features Ilt</title><imprint><publisher>North Holland</publisher><date type="published" when="1992"></date><biblScope unit="page" from="29" to="40"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b10"><analytic><title level="a" type="main">Special issue on document image analysis systems</title><author><persName><forename type="first">O '</forename><surname>Gorman</surname></persName></author><author><persName><forename type="first">L</forename><surname>Kasturi</surname></persName></author><author><persName><forename type="first">R</forename></persName></author></analytic><monogr><title level="j">tEEE Computer</title><imprint><biblScope unit="volume">25</biblScope><biblScope unit="issue">7</biblScope><date type="published" when="1992"></date></imprint></monogr></biblStruct><biblStruct xml:id="b11"><analytic><title level="a" type="main">Offline tracing and representation of signatures</title><author><persName><forename type="first">J</forename><forename type="middle">C</forename><surname>Pan</surname></persName></author><author><persName><forename type="first">S</forename><surname>Lee</surname></persName></author></analytic><monogr><title level="m">Proceedings of Computer Vision and Pattern Recognition</title><meeting>Computer Vision and Pattern Recognition</meeting><imprint><date type="published" when="1991"></date><biblScope unit="page" from="679" to="680"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b12"><analytic><title level="a" type="main">Special issue on optical character recognition</title><author><persName><forename type="first">T</forename><surname>Pavlidis</surname></persName></author><author><persName><forename type="first">S</forename><surname>Mori</surname></persName></author></analytic><monogr><title level="j">Proceedings of the IEEE</title><imprint><biblScope unit="volume">80</biblScope><biblScope unit="issue">7</biblScope><date type="published" when="1992"></date></imprint></monogr></biblStruct><biblStruct xml:id="b13"><analytic><title level="a" type="main">Regularities and singularities</title><author><persName><forename type="first">J</forename><forename type="middle">C</forename><surname>Simon</surname></persName></author><author><persName><forename type="first">O</forename><surname>Baret</surname></persName></author></analytic><monogr><title level="j">International Journal o¢7~attern Recognition and Artificial Intelligence</title><imprint><biblScope unit="volume">5</biblScope><biblScope unit="page" from="57" to="77"></biblScope><date type="published" when="1991"></date></imprint></monogr></biblStruct><biblStruct xml:id="b14"><analytic><title level="a" type="main">Delermination of the direction of ballpoint pen motion from the orientations of burr striations in curved pen strokes</title><author><persName><forename type="first">K</forename><forename type="middle">W</forename><surname>Snape</surname></persName></author></analytic><monogr><title level="j">Journal of Forensic Sciences</title><imprint><biblScope unit="volume">25</biblScope><biblScope unit="page" from="386" to="390"></biblScope><date type="published" when="1980"></date></imprint></monogr></biblStruct><biblStruct xml:id="b15"><analytic><title level="a" type="main">A thinning method based on cell structure</title><author><persName><forename type="first">T</forename><surname>Suzuki</surname></persName></author><author><persName><forename type="first">S</forename><surname>Mori</surname></persName></author></analytic><monogr><title level="m">Proceedings of the International Wbrlarhop on Frontiers in Handwriting Recognition</title><meeting>the International Wbrlarhop on Frontiers in Handwriting Recognition</meeting><imprint><date type="published" when="1990"></date><biblScope unit="page" from="39" to="52"></biblScope></imprint></monogr></biblStruct><biblStruct xml:id="b16"><analytic><title level="a" type="main">The state of the art in on-line handwriting recognition--a survey</title><author><persName><forename type="first">C</forename><forename type="middle">C</forename><surname>Tappert</surname></persName></author><author><persName><forename type="first">C</forename><forename type="middle">Y</forename><surname>Suen</surname></persName></author><author><persName><forename type="first">T</forename><surname>Wakahara</surname></persName></author></analytic><monogr><title level="j">IEEE Transactions on Pattern Analysis and Machine Intelligence</title><imprint><biblScope unit="volume">12</biblScope><biblScope unit="page" from="878" to="808"></biblScope><date type="published" when="1990"></date></imprint></monogr></biblStruct></listBibl></back></text></istex:refBibTEI></enrichments><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000885 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000885 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= OcrV1
|flux= Istex
|étape= Corpus
|type= RBID
|clé= ISTEX:C1B04C00CC4642C16E5DBD5475B80960837B2BF4
|texte= Recovery of temporal information from static images of handwriting
}}
| This area was generated with Dilib version V0.6.32. |  |