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Conference Paper: An off-line large vocabulary hand-written Chinese character recognizer
Title | An off-line large vocabulary hand-written Chinese character recognizer |
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Authors | |
Keywords | Computers Computer graphics |
Issue Date | 1997 |
Publisher | IEEE. |
Citation | International Conference on Image Processing Proceedings, Santa Barbara, CA, USA, 26-29 October 1997, v. 3, p. 324-327 How to Cite? |
Abstract | An off-line hand-written Chinese character recognizer based on contextual vector quantization (CVQ) supporting a vocabulary of 4616 Chinese characters, alphanumerics and punctuation symbols has been reported. Trained with a sample for each character from each of 100 writers and tested on texts of 160000 characters written by another 200 writers, the average recognition rate is 77.2%. Two statistical language models have been investigated in this study. Their performance in terms of their capabilities in upgrading the recognition rate by 8.8% and 12.0% respectively when used as post-processors of the recognizer are reported. |
Persistent Identifier | http://hdl.handle.net/10722/45599 |
ISBN |
DC Field | Value | Language |
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dc.contributor.author | Wong, PK | en_HK |
dc.contributor.author | Chan, C | en_HK |
dc.date.accessioned | 2007-10-30T06:30:01Z | - |
dc.date.available | 2007-10-30T06:30:01Z | - |
dc.date.issued | 1997 | en_HK |
dc.identifier.citation | International Conference on Image Processing Proceedings, Santa Barbara, CA, USA, 26-29 October 1997, v. 3, p. 324-327 | en_HK |
dc.identifier.isbn | 0-8186-8183-7 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/45599 | - |
dc.description.abstract | An off-line hand-written Chinese character recognizer based on contextual vector quantization (CVQ) supporting a vocabulary of 4616 Chinese characters, alphanumerics and punctuation symbols has been reported. Trained with a sample for each character from each of 100 writers and tested on texts of 160000 characters written by another 200 writers, the average recognition rate is 77.2%. Two statistical language models have been investigated in this study. Their performance in terms of their capabilities in upgrading the recognition rate by 8.8% and 12.0% respectively when used as post-processors of the recognizer are reported. | en_HK |
dc.format.extent | 431599 bytes | - |
dc.format.extent | 3669 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.rights | ©1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Computers | en_HK |
dc.subject | Computer graphics | en_HK |
dc.title | An off-line large vocabulary hand-written Chinese character recognizer | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0-8186-8183-7&volume=3&spage=324&epage=327&date=1997&atitle=An+off-line+large+vocabulary+hand-written+Chinese+character+recognizer | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/ICIP.1997.632106 | en_HK |
dc.identifier.hkuros | 38206 | - |