DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sin, BK | ko |
dc.contributor.author | Kim, JinHyung | ko |
dc.date.accessioned | 2013-03-03T04:47:24Z | - |
dc.date.available | 2013-03-03T04:47:24Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1998-03 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, v.12, no.2, pp.233 - 249 | - |
dc.identifier.issn | 0218-0014 | - |
dc.identifier.uri | http://hdl.handle.net/10203/77289 | - |
dc.description.abstract | It is well known that the stochastic approach using the HMM and dynamic programming-based search is particularly suited to the analysis of time series signals including on-line handwriting. The starting point of this research is a network of HMMs which models the whole set of characters. Then it is followed by the assertion that the HMM for the on-line script can be applied to not only on-line character recognition but also to the handwriting synthesis and even pen-trajectory recovery in off-line character images. The solutions to these problems are based on the single network of HMMs and the single principle of DP-based state-observation alignment. Given an observation sequence, the search for the best path in the network corresponds to the recognition. Given a character model, the search for the best observation sequence corresponds to the handwriting generation. The proposed framework has been shown to work nicely through a set of tests on Korean characters. | - |
dc.language | English | - |
dc.publisher | WORLD SCIENTIFIC PUBL CO PTE LTD | - |
dc.subject | RECOGNITION | - |
dc.title | Network-based approach to Korean handwriting analysis | - |
dc.type | Article | - |
dc.identifier.wosid | 000073849600006 | - |
dc.identifier.scopusid | 2-s2.0-0242719504 | - |
dc.type.rims | ART | - |
dc.citation.volume | 12 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 233 | - |
dc.citation.endingpage | 249 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | - |
dc.contributor.localauthor | Kim, JinHyung | - |
dc.contributor.nonIdAuthor | Sin, BK | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | character recognition | - |
dc.subject.keywordAuthor | handwriting generation | - |
dc.subject.keywordAuthor | pen trajectory recovery | - |
dc.subject.keywordAuthor | hidden Markov model | - |
dc.subject.keywordAuthor | Viterbi algorithm | - |
dc.subject.keywordAuthor | Korean character | - |
dc.subject.keywordPlus | RECOGNITION | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.