Building a new generation of handwriting recognition systems
Identifieur interne : 003183 ( Main/Merge ); précédent : 003182; suivant : 003184Building a new generation of handwriting recognition systems
Auteurs : C. Y. Suen [Canada] ; R. Legault [Canada] ; C. Nadal [Canada] ; M. Cheriet [Canada] ; L. Lam [Canada]Source :
- 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
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Lam</name></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><idno type="wicri:Area/Istex/Curation">001387</idno><idno type="wicri:Area/Istex/Checkpoint">002272</idno><idno type="wicri:doubleKey">0167-8655:1993:Suen C:building:a:new</idno><idno type="wicri:Area/Main/Merge">003183</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 wicri:level="3"><country>Canada</country><wicri:regionArea>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName></affiliation></author><author><name sortKey="Legault, R" sort="Legault, R" uniqKey="Legault R" first="R." last="Legault">R. Legault</name><affiliation wicri:level="3"><country>Canada</country><wicri:regionArea>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName></affiliation></author><author><name sortKey="Nadal, C" sort="Nadal, C" uniqKey="Nadal C" first="C." last="Nadal">C. Nadal</name><affiliation wicri:level="3"><country>Canada</country><wicri:regionArea>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName></affiliation></author><author><name sortKey="Cheriet, M" sort="Cheriet, M" uniqKey="Cheriet M" first="M." last="Cheriet">M. Cheriet</name><affiliation wicri:level="3"><country>Canada</country><wicri:regionArea>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName></affiliation></author><author><name sortKey="Lam, L" sort="Lam, L" uniqKey="Lam L" first="L." last="Lam">L. Lam</name><affiliation wicri:level="3"><country>Canada</country><wicri:regionArea>Centre for Pattern Recognition & Machine Intelligence, Concordia University, Montréal</wicri:regionArea><placeName><settlement type="city">Montréal</settlement><region type="state">Québec</region></placeName></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></record>Pour manipuler ce document sous Unix (Dilib)
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