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  • 标题:Online Farsi Handwritten Character Recognition Using Hidden Markov Model
  • 其他标题:Online Farsi Handwritten Character Recognition Using Hidden Markov Model
  • 本地全文:下载
  • 作者:Vahid Ghods ; Mohammad Karim Sohrabi
  • 期刊名称:Journal of Computers
  • 印刷版ISSN:1796-203X
  • 出版年度:2016
  • 卷号:11
  • 期号:2
  • 页码:169-175
  • DOI:10.17706/jcp.11.2.169-175
  • 出版社:Academy Publisher
  • 摘要:In this paper, a method for recognizing online Farsi characters that are written separately has been introduced. Regarding to the shape and the structure of the main body, Farsi letters have been divided into 18 groups. First, hidden Markov model (HMM) technique has been exploited to recognize the main body. In the next step, the final recognition in each group is performed according to delayed strokes (dots and small signs) and their hidden Markov models. The proposed method has been tested on TMU dataset and the recognition accuracy of 95.9% and 94.2% has been obtained for the recognition of the group and the character, respectively.
  • 其他关键词:Character recognition, Farsi, Persian, online handwriting, HMM.
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