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DC Field | Value | Language |
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dc.contributor.author | Zeng, Jia (曾嘉) | |
dc.contributor.author | Liu, Zhi-Qiang | |
dc.date.accessioned | 2006-04-25T08:24:35Z | |
dc.date.accessioned | 2017-09-19T09:18:39Z | |
dc.date.accessioned | 2019-02-12T08:44:04Z | - |
dc.date.available | 2006-04-25T08:24:35Z | |
dc.date.available | 2017-09-19T09:18:39Z | |
dc.date.available | 2019-02-12T08:44:04Z | - |
dc.date.issued | 2006-03 | |
dc.identifier.other | scm2006-001 | |
dc.identifier.uri | http://144.214.8.231/handle/2031/793 | - |
dc.description.abstract | In this paper, we propose a statistical-structural scheme for Chinese character modeling based on Markov random fields (MRFs). We use 2-D Gabor filters to extract directional stroke segments from images of Chinese characters, where each stroke segment is associated with a state in Markov random field models. The structural information is described by neighborhood system and pair-state clique potentials; meanwhile the statistical information is represented by single-state probability density functions (pdfs). Extensive experiments on similar characters have been carried out on the database ETL9B. The experimental results confirm that Markov random field models are effective in modeling both statistical and structural information of Chinese characters, and works well for handwritten Chinese character recognition. | |
dc.format.extent | 169 bytes | |
dc.format.mimetype | text/html | |
dc.rights | This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner. | |
dc.title | Markov random fields for handwritten Chinese character recognition | en |
dc.type | Article | en |
dc.contributor.department | School of Creative Media (Zeng, J.; Prof. Liu, Z. Q.) | en |
dc.description.award | Won the Second Prize (Postgraduate Section) in the IEEE Hong Kong Section Student Paper Contest 2005. | en |
dc.description.remark | The Institutional Repository only contains the News announcement | |
Appears in Collections: | Student Works With External Awards |
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award_news.html | 169 B | HTML | View/Open |
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