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Online Handwriting Character Recognition Method Using Directional and Direction-Change Features.

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Title: Online Handwriting Character Recognition Method Using Directional and Direction-Change Features.
Authors: Okamoto, Masayoshi, Yamamoto, Kazuhiko
Source: International Journal of Pattern Recognition & Artificial Intelligence. Nov1999, Vol. 13 Issue 7, p1041. 19p.
Subjects: Pattern perception, Japanese character sets (Data processing)
Abstract: We propose a new online recognition method to recognize handwritten cursive-style Japanese characters correctly. Our method simultaneously uses both directional features, otherwise known as offline features, and direction-change features which we designed as online features. The direction-change features express where in the mesh and in which direction the character's coordinates change. These features express both written strokes in the pen-down state and unwritten imaginary strokes in the pen-up state. The recognition rate was improved by our method over the traditional method using only directional features. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company 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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Header DbId: egs
DbLabel: Engineering Source
An: 10236485
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
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  Data: Online Handwriting Character Recognition Method Using Directional and Direction-Change Features.
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  Data: <searchLink fieldCode="AR" term="%22Okamoto%2C+Masayoshi%22">Okamoto, Masayoshi</searchLink><br /><searchLink fieldCode="AR" term="%22Yamamoto%2C+Kazuhiko%22">Yamamoto, Kazuhiko</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Pattern+perception%22">Pattern perception</searchLink><br /><searchLink fieldCode="DE" term="%22Japanese+character+sets+%28Data+processing%29%22">Japanese character sets (Data processing)</searchLink>
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  Label: Abstract
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  Data: We propose a new online recognition method to recognize handwritten cursive-style Japanese characters correctly. Our method simultaneously uses both directional features, otherwise known as offline features, and direction-change features which we designed as online features. The direction-change features express where in the mesh and in which direction the character's coordinates change. These features express both written strokes in the pen-down state and unwritten imaginary strokes in the pen-up state. The recognition rate was improved by our method over the traditional method using only directional features. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company 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: 10.1142/S0218001499000586
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 19
        StartPage: 1041
    Subjects:
      – SubjectFull: Pattern perception
        Type: general
      – SubjectFull: Japanese character sets (Data processing)
        Type: general
    Titles:
      – TitleFull: Online Handwriting Character Recognition Method Using Directional and Direction-Change Features.
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          Name:
            NameFull: Okamoto, Masayoshi
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          Name:
            NameFull: Yamamoto, Kazuhiko
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          Dates:
            – D: 01
              M: 11
              Text: Nov1999
              Type: published
              Y: 1999
          Identifiers:
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              Value: 02180014
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              Value: 13
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              Value: 7
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            – TitleFull: International Journal of Pattern Recognition & Artificial Intelligence
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