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Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models.

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Title: Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models.
Authors: Shi, D., Gunn, S.R., Damper, R.I.
Source: IEEE Transactions on Pattern Analysis & Machine Intelligence. Feb2003, Vol. 25 Issue 2, p277. 4p. 3 Diagrams, 1 Chart.
Subjects: Chinese character sets (Data processing), Mathematical transformations
Abstract: Handwritten Chinese characters can be recognized by first extracting the basic shapes (radicals) of which they are composed, Radicals are described by nonlinear active shape models and optimal parameters found using the chamfer distance transform and a dynamic tunneling algorithm. The radical recognition rate is 96.5 percent correct (writer-independent) on 280,000 characters containing 98 radical classes. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Pattern Analysis & Machine Intelligence is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 9066370
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  Data: Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models.
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  Data: <searchLink fieldCode="DE" term="%22Chinese+character+sets+%28Data+processing%29%22">Chinese character sets (Data processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+transformations%22">Mathematical transformations</searchLink>
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  Data: Handwritten Chinese characters can be recognized by first extracting the basic shapes (radicals) of which they are composed, Radicals are described by nonlinear active shape models and optimal parameters found using the chamfer distance transform and a dynamic tunneling algorithm. The radical recognition rate is 96.5 percent correct (writer-independent) on 280,000 characters containing 98 radical classes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Pattern Analysis & Machine Intelligence is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1109/TPAMI.2003.1177158
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      – Code: eng
        Text: English
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        PageCount: 4
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      – SubjectFull: Mathematical transformations
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      – TitleFull: Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models.
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            NameFull: Shi, D.
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            NameFull: Gunn, S.R.
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              Text: Feb2003
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              Y: 2003
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