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  • 标题:Invariant and Zernike Based Offline Handwritten Character Recognition
  • 本地全文:下载
  • 作者:S.Sangeetha Devi ; T.Amitha
  • 期刊名称:International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
  • 印刷版ISSN:2278-1323
  • 出版年度:2014
  • 卷号:3
  • 期号:5
  • 页码:1950-1954
  • 出版社:Shri Pannalal Research Institute of Technolgy
  • 摘要:Character recognition is one of the tough method processes attributable to the nice variations of writing styles, fully totally different size and orientation angle of the characters. Many researchers are specializing in recognizing written digits and characters in many languages. To the foremost effective of our data, little work has been done in the realm of Tamil written character recognition which they experimented with their own data. The invariant written character recognition is tougher. This paper introduced and evaluated utterly completely different shape-based image invariants from the perspective of their invariability property to image transformations in addition as scaling, translation, rotation and completely different image spatial resolutions. To appreciate these ideas, we've got an inclination to use Hu's and Zernike moment as feature. The proposing system analysis the features in the character and trains itself to identify and recognize the invariant characters using the previously learned data.
  • 关键词:Optical Character Recognition; Online Handwritten ; Recognition; Offline Handwritten Recognition; Hu's Moment; ; Zernike Moment; Artificial Neural Network
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