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On-line cursive Kanji character recognition using stroke-based affine transformation

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2 Author(s)
Wakahara, T. ; NTT Human Interface Labs., Nippon Telegraph & Telephone Corp., Kanagawa, Japan ; Odaka, K.

We present a distortion-tolerant online cursive Kanji character recognition method that absorbs the stroke-based handwriting distortion expressible by uniform affine transformation. Experiments are made using two kinds of test data in the square style and in the cursive style for 2,980 Kanji character categories; recognition rates of 98.4 percent and 96.0 percent are obtained

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:19 ,  Issue: 12 )