Building a new generation of handwriting recognition systems
Identifieur interne : 001473 ( Istex/Corpus ); précédent : 001472; suivant : 001474Building a new generation of handwriting recognition systems
Auteurs : C. Y. Suen ; R. Legault ; C. Nadal ; M. Cheriet ; L. LamSource :
- Pattern Recognition Letters [ 0167-8655 ] ; 1992.
Abstract
This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.
Url:
DOI: 10.1016/0167-8655(93)90096-V
Links to Exploration step
ISTEX:5C6E70A1EFD415796307D264152A13F20918E0C9Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title>Building a new generation of handwriting recognition systems</title>
<author><name sortKey="Suen, C Y" sort="Suen, C Y" uniqKey="Suen C" first="C. Y." last="Suen">C. Y. Suen</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Legault, R" sort="Legault, R" uniqKey="Legault R" first="R." last="Legault">R. Legault</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Nadal, C" sort="Nadal, C" uniqKey="Nadal C" first="C." last="Nadal">C. Nadal</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Cheriet, M" sort="Cheriet, M" uniqKey="Cheriet M" first="M." last="Cheriet">M. Cheriet</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Lam, L" sort="Lam, L" uniqKey="Lam L" first="L." last="Lam">L. Lam</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:5C6E70A1EFD415796307D264152A13F20918E0C9</idno>
<date when="1993" year="1993">1993</date>
<idno type="doi">10.1016/0167-8655(93)90096-V</idno>
<idno type="url">https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">001473</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a">Building a new generation of handwriting recognition systems</title>
<author><name sortKey="Suen, C Y" sort="Suen, C Y" uniqKey="Suen C" first="C. Y." last="Suen">C. Y. Suen</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Legault, R" sort="Legault, R" uniqKey="Legault R" first="R." last="Legault">R. Legault</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Nadal, C" sort="Nadal, C" uniqKey="Nadal C" first="C." last="Nadal">C. Nadal</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Cheriet, M" sort="Cheriet, M" uniqKey="Cheriet M" first="M." last="Cheriet">M. Cheriet</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
<author><name sortKey="Lam, L" sort="Lam, L" uniqKey="Lam L" first="L." last="Lam">L. Lam</name>
<affiliation><mods:affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</mods:affiliation>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="j">Pattern Recognition Letters</title>
<title level="j" type="abbrev">PATREC</title>
<idno type="ISSN">0167-8655</idno>
<imprint><publisher>ELSEVIER</publisher>
<date type="published" when="1992">1992</date>
<biblScope unit="volume">14</biblScope>
<biblScope unit="issue">4</biblScope>
<biblScope unit="page" from="303">303</biblScope>
<biblScope unit="page" to="315">315</biblScope>
</imprint>
<idno type="ISSN">0167-8655</idno>
</series>
<idno type="istex">5C6E70A1EFD415796307D264152A13F20918E0C9</idno>
<idno type="DOI">10.1016/0167-8655(93)90096-V</idno>
<idno type="PII">0167-8655(93)90096-V</idno>
</biblStruct>
</sourceDesc>
<seriesStmt><idno type="ISSN">0167-8655</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass></textClass>
<langUsage><language ident="en">en</language>
</langUsage>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.</div>
</front>
</TEI>
<istex><corpusName>elsevier</corpusName>
<author><json:item><name>C.Y. Suen</name>
<affiliations><json:string>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</json:string>
</affiliations>
</json:item>
<json:item><name>R. Legault</name>
<affiliations><json:string>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</json:string>
</affiliations>
</json:item>
<json:item><name>C. Nadal</name>
<affiliations><json:string>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</json:string>
</affiliations>
</json:item>
<json:item><name>M. Cheriet</name>
<affiliations><json:string>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</json:string>
</affiliations>
</json:item>
<json:item><name>L. Lam</name>
<affiliations><json:string>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</json:string>
</affiliations>
</json:item>
</author>
<subject><json:item><lang><json:string>eng</json:string>
</lang>
<value>Handwriting recognition</value>
</json:item>
<json:item><lang><json:string>eng</json:string>
</lang>
<value>feature extraction</value>
</json:item>
<json:item><lang><json:string>eng</json:string>
</lang>
<value>improving handwriting recognizers, recognition by experts</value>
</json:item>
</subject>
<language><json:string>eng</json:string>
</language>
<abstract>This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.</abstract>
<qualityIndicators><score>6.056</score>
<pdfVersion>1.2</pdfVersion>
<pdfPageSize>548 x 749 pts</pdfPageSize>
<refBibsNative>true</refBibsNative>
<keywordCount>3</keywordCount>
<abstractCharCount>598</abstractCharCount>
<pdfWordCount>7236</pdfWordCount>
<pdfCharCount>44369</pdfCharCount>
<pdfPageCount>13</pdfPageCount>
<abstractWordCount>88</abstractWordCount>
</qualityIndicators>
<title>Building a new generation of handwriting recognition systems</title>
<pii><json:string>0167-8655(93)90096-V</json:string>
</pii>
<genre><json:string>research-article</json:string>
</genre>
<serie><genre></genre>
<language><json:string>unknown</json:string>
</language>
<title>Technical report</title>
</serie>
<host><volume>14</volume>
<pii><json:string>S0167-8655(00)X0108-0</json:string>
</pii>
<pages><last>315</last>
<first>303</first>
</pages>
<issn><json:string>0167-8655</json:string>
</issn>
<issue>4</issue>
<genre><json:string>Journal</json:string>
</genre>
<language><json:string>unknown</json:string>
</language>
<title>Pattern Recognition Letters</title>
<publicationDate>1993</publicationDate>
</host>
<categories><wos><json:string>COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE</json:string>
</wos>
</categories>
<publicationDate>1992</publicationDate>
<copyrightDate>1993</copyrightDate>
<doi><json:string>10.1016/0167-8655(93)90096-V</json:string>
</doi>
<id>5C6E70A1EFD415796307D264152A13F20918E0C9</id>
<fulltext><json:item><original>true</original>
<mimetype>application/pdf</mimetype>
<extension>pdf</extension>
<uri>https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/fulltext/pdf</uri>
</json:item>
<json:item><original>true</original>
<mimetype>text/plain</mimetype>
<extension>txt</extension>
<uri>https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/fulltext/txt</uri>
</json:item>
<json:item><original>false</original>
<mimetype>application/zip</mimetype>
<extension>zip</extension>
<uri>https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/fulltext/zip</uri>
</json:item>
<istex:fulltextTEI uri="https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Building a new generation of handwriting recognition systems</title>
</titleStmt>
<publicationStmt><authority>ISTEX</authority>
<publisher>ELSEVIER</publisher>
<availability><p>ELSEVIER</p>
</availability>
<date>1993</date>
</publicationStmt>
<sourceDesc><biblStruct type="inbook"><analytic><title level="a">Building a new generation of handwriting recognition systems</title>
<author><persName><forename type="first">C.Y.</forename>
<surname>Suen</surname>
</persName>
<note type="correspondence"><p>Correspondence to: C.Y. Suen, Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8.</p>
</note>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
</author>
<author><persName><forename type="first">R.</forename>
<surname>Legault</surname>
</persName>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
</author>
<author><persName><forename type="first">C.</forename>
<surname>Nadal</surname>
</persName>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
</author>
<author><persName><forename type="first">M.</forename>
<surname>Cheriet</surname>
</persName>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
</author>
<author><persName><forename type="first">L.</forename>
<surname>Lam</surname>
</persName>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
</author>
</analytic>
<monogr><title level="j">Pattern Recognition Letters</title>
<title level="j" type="abbrev">PATREC</title>
<idno type="pISSN">0167-8655</idno>
<idno type="PII">S0167-8655(00)X0108-0</idno>
<imprint><publisher>ELSEVIER</publisher>
<date type="published" when="1992"></date>
<biblScope unit="volume">14</biblScope>
<biblScope unit="issue">4</biblScope>
<biblScope unit="page" from="303">303</biblScope>
<biblScope unit="page" to="315">315</biblScope>
</imprint>
</monogr>
<idno type="istex">5C6E70A1EFD415796307D264152A13F20918E0C9</idno>
<idno type="DOI">10.1016/0167-8655(93)90096-V</idno>
<idno type="PII">0167-8655(93)90096-V</idno>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><creation><date>1993</date>
</creation>
<langUsage><language ident="en">en</language>
</langUsage>
<abstract xml:lang="en"><p>This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.</p>
</abstract>
<textClass><keywords scheme="keyword"><list><head>Keywords</head>
<item><term>Handwriting recognition</term>
</item>
<item><term>feature extraction</term>
</item>
<item><term>improving handwriting recognizers, recognition by experts</term>
</item>
</list>
</keywords>
</textClass>
</profileDesc>
<revisionDesc><change when="1992-02-28">Received</change>
<change when="1992-11-24">Modified</change>
<change when="1992">Published</change>
</revisionDesc>
</teiHeader>
</istex:fulltextTEI>
</fulltext>
<metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration>
<istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"></istex:docType>
<istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>PATREC</jid>
<aid>9390096V</aid>
<ce:pii>0167-8655(93)90096-V</ce:pii>
<ce:doi>10.1016/0167-8655(93)90096-V</ce:doi>
<ce:copyright type="unknown" year="1993"></ce:copyright>
</item-info>
<head><ce:title>Building a new generation of handwriting recognition systems</ce:title>
<ce:author-group><ce:author><ce:given-name>C.Y.</ce:given-name>
<ce:surname>Suen</ce:surname>
<ce:cross-ref refid="COR1"><ce:sup>∗</ce:sup>
</ce:cross-ref>
</ce:author>
<ce:author><ce:given-name>R.</ce:given-name>
<ce:surname>Legault</ce:surname>
</ce:author>
<ce:author><ce:given-name>C.</ce:given-name>
<ce:surname>Nadal</ce:surname>
</ce:author>
<ce:author><ce:given-name>M.</ce:given-name>
<ce:surname>Cheriet</ce:surname>
</ce:author>
<ce:author><ce:given-name>L.</ce:given-name>
<ce:surname>Lam</ce:surname>
</ce:author>
<ce:affiliation><ce:textfn>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</ce:textfn>
</ce:affiliation>
<ce:correspondence id="COR1"><ce:label>∗</ce:label>
<ce:text><ce:italic>Correspondence to:</ce:italic>
C.Y. Suen, Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8.</ce:text>
</ce:correspondence>
</ce:author-group>
<ce:date-received day="28" month="2" year="1992"></ce:date-received>
<ce:date-revised day="24" month="11" year="1992"></ce:date-revised>
<ce:abstract><ce:section-title>Abstract</ce:section-title>
<ce:abstract-sec><ce:simple-para>This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.</ce:simple-para>
</ce:abstract-sec>
</ce:abstract>
<ce:keywords><ce:section-title>Keywords</ce:section-title>
<ce:keyword><ce:text>Handwriting recognition</ce:text>
</ce:keyword>
<ce:keyword><ce:text>feature extraction</ce:text>
</ce:keyword>
<ce:keyword><ce:text>improving handwriting recognizers, recognition by experts</ce:text>
</ce:keyword>
</ce:keywords>
</head>
</converted-article>
</istex:document>
</istex:metadataXml>
<mods version="3.6"><titleInfo><title>Building a new generation of handwriting recognition systems</title>
</titleInfo>
<titleInfo type="alternative" contentType="CDATA"><title>Building a new generation of handwriting recognition systems</title>
</titleInfo>
<name type="personal"><namePart type="given">C.Y.</namePart>
<namePart type="family">Suen</namePart>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
<description>Correspondence to: C.Y. Suen, Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8.</description>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">R.</namePart>
<namePart type="family">Legault</namePart>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">C.</namePart>
<namePart type="family">Nadal</namePart>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">M.</namePart>
<namePart type="family">Cheriet</namePart>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<name type="personal"><namePart type="given">L.</namePart>
<namePart type="family">Lam</namePart>
<affiliation>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal, Canada H3G 1M8</affiliation>
<role><roleTerm type="text">author</roleTerm>
</role>
</name>
<typeOfResource>text</typeOfResource>
<genre type="research-article" displayLabel="Full-length article"></genre>
<originInfo><publisher>ELSEVIER</publisher>
<dateIssued encoding="w3cdtf">1992</dateIssued>
<dateCaptured encoding="w3cdtf">1992-02-28</dateCaptured>
<dateModified encoding="w3cdtf">1992-11-24</dateModified>
<copyrightDate encoding="w3cdtf">1993</copyrightDate>
</originInfo>
<language><languageTerm type="code" authority="iso639-2b">eng</languageTerm>
<languageTerm type="code" authority="rfc3066">en</languageTerm>
</language>
<physicalDescription><internetMediaType>text/html</internetMediaType>
</physicalDescription>
<abstract lang="en">This paper gives an assessment of the current state of the art in handwriting recognition. It summarizes the lessons learned, the difficulties involved, and the challenges ahead. Based on a review of the recent achievements in off-line computer recognition of totally unconstrained handwritten characters, and extensive research, the authors attempt to identify new frontiers for research which may lead to further breakthroughs in this field. They will present some evidences and novel ideas on ways of stretching the limits of handwriting recognition systems aiming at outperforming human beings.</abstract>
<subject><genre>Keywords</genre>
<topic>Handwriting recognition</topic>
<topic>feature extraction</topic>
<topic>improving handwriting recognizers, recognition by experts</topic>
</subject>
<relatedItem type="host"><titleInfo><title>Pattern Recognition Letters</title>
</titleInfo>
<titleInfo type="abbreviated"><title>PATREC</title>
</titleInfo>
<genre type="Journal">journal</genre>
<originInfo><dateIssued encoding="w3cdtf">199304</dateIssued>
</originInfo>
<identifier type="ISSN">0167-8655</identifier>
<identifier type="PII">S0167-8655(00)X0108-0</identifier>
<part><date>199304</date>
<detail type="issue"><title>Postal Processing and Character Recognition</title>
</detail>
<detail type="volume"><number>14</number>
<caption>vol.</caption>
</detail>
<detail type="issue"><number>4</number>
<caption>no.</caption>
</detail>
<extent unit="issue pages"><start>257</start>
<end>354</end>
</extent>
<extent unit="pages"><start>303</start>
<end>315</end>
</extent>
</part>
</relatedItem>
<identifier type="istex">5C6E70A1EFD415796307D264152A13F20918E0C9</identifier>
<identifier type="DOI">10.1016/0167-8655(93)90096-V</identifier>
<identifier type="PII">0167-8655(93)90096-V</identifier>
<recordInfo><recordContentSource>ELSEVIER</recordContentSource>
</recordInfo>
</mods>
</metadata>
<enrichments><istex:catWosTEI uri="https://api.istex.fr/document/5C6E70A1EFD415796307D264152A13F20918E0C9/enrichments/catWos"><teiHeader><profileDesc><textClass><classCode scheme="WOS">COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE</classCode>
</textClass>
</profileDesc>
</teiHeader>
</istex:catWosTEI>
</enrichments>
</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 001473 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 001473 | 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:5C6E70A1EFD415796307D264152A13F20918E0C9 |texte= Building a new generation of handwriting recognition systems }}
![]() | This area was generated with Dilib version V0.6.32. | ![]() |