Off-line recognition of cursive script produced by a cooperative writer
A method for the off-line recognition of cursive handwriting based on hidden Markov models is described. The features used in the HMMs are based on the arcs of skeleton graphs of the words to be recognized. An average correct recognition rate of over 98% on the word level has been achieved in experi...
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creator | Bunke, H. Roth, M. Schukat-Talamazzini, E.G. |
description | A method for the off-line recognition of cursive handwriting based on hidden Markov models is described. The features used in the HMMs are based on the arcs of skeleton graphs of the words to be recognized. An average correct recognition rate of over 98% on the word level has been achieved in experiments with cooperative writers using two dictionaries of 150 words each. |
doi_str_mv | 10.1109/ICPR.1994.576948 |
format | Conference Proceeding |
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The features used in the HMMs are based on the arcs of skeleton graphs of the words to be recognized. An average correct recognition rate of over 98% on the word level has been achieved in experiments with cooperative writers using two dictionaries of 150 words each.</description><identifier>ISBN: 9780818662706</identifier><identifier>ISBN: 0818662700</identifier><identifier>DOI: 10.1109/ICPR.1994.576948</identifier><language>eng</language><publisher>IEEE</publisher><subject>Application software ; Character recognition ; Dictionaries ; Handwriting recognition ; Hidden Markov models ; Optical character recognition software ; Postal services ; Skeleton ; Speech recognition ; Writing</subject><ispartof>Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. 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An average correct recognition rate of over 98% on the word level has been achieved in experiments with cooperative writers using two dictionaries of 150 words each.</description><subject>Application software</subject><subject>Character recognition</subject><subject>Dictionaries</subject><subject>Handwriting recognition</subject><subject>Hidden Markov models</subject><subject>Optical character recognition software</subject><subject>Postal services</subject><subject>Skeleton</subject><subject>Speech recognition</subject><subject>Writing</subject><isbn>9780818662706</isbn><isbn>0818662700</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1994</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj0tLAzEYRQMiKHX24ip_YMa8H0sZtBYKFdF1yWS-SKROhiRV-u8dqXdz4XC4cBG6paSjlNj7Tf_y2lFrRSe1ssJcoMZqQww1SjFN1BVqSvkkS6RckLlG610I7SFOgDP49DHFGtOEU8D-mEv8Blx8jnPFc07j0cOIhxN22Kc0Q3b1T_jJsUK-QZfBHQo0_71C70-Pb_1zu92tN_3Dto1Us9oKRT21erR-IIFQz8UofZBSB26YAiLBEKdGpoIUmrFB8wVY6phXJgwa-ArdnXcjAOznHL9cPu3Pb_kvpLFKoQ</recordid><startdate>1994</startdate><enddate>1994</enddate><creator>Bunke, H.</creator><creator>Roth, M.</creator><creator>Schukat-Talamazzini, E.G.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1994</creationdate><title>Off-line recognition of cursive script produced by a cooperative writer</title><author>Bunke, H. ; Roth, M. ; Schukat-Talamazzini, E.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i172t-461c197d9cb0f01c34d5cf557f3826e05e80a6d26f54722b73e8091a2c68fb7e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Application software</topic><topic>Character recognition</topic><topic>Dictionaries</topic><topic>Handwriting recognition</topic><topic>Hidden Markov models</topic><topic>Optical character recognition software</topic><topic>Postal services</topic><topic>Skeleton</topic><topic>Speech recognition</topic><topic>Writing</topic><toplevel>online_resources</toplevel><creatorcontrib>Bunke, H.</creatorcontrib><creatorcontrib>Roth, M.</creatorcontrib><creatorcontrib>Schukat-Talamazzini, E.G.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bunke, H.</au><au>Roth, M.</au><au>Schukat-Talamazzini, E.G.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Off-line recognition of cursive script produced by a cooperative writer</atitle><btitle>Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5)</btitle><stitle>ICPR</stitle><date>1994</date><risdate>1994</risdate><volume>2</volume><spage>383</spage><epage>386 vol.2</epage><pages>383-386 vol.2</pages><isbn>9780818662706</isbn><isbn>0818662700</isbn><abstract>A method for the off-line recognition of cursive handwriting based on hidden Markov models is described. The features used in the HMMs are based on the arcs of skeleton graphs of the words to be recognized. An average correct recognition rate of over 98% on the word level has been achieved in experiments with cooperative writers using two dictionaries of 150 words each.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.1994.576948</doi></addata></record> |
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ispartof | Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5), 1994, Vol.2, p.383-386 vol.2 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Application software Character recognition Dictionaries Handwriting recognition Hidden Markov models Optical character recognition software Postal services Skeleton Speech recognition Writing |
title | Off-line recognition of cursive script produced by a cooperative writer |
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