On-Line Cursive Kanji Character Recognition Using Stroke-Based Affine Transformation

Authors:
Toru Wakahara;Kazumi Odaka
Affiliations:
Nippan Telegraph and Telephone Corporation, Kanagawa, Japan;Univ. of Library and Information Science, Ibaraki, Japan
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1997

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Abstract

We present a distortion-tolerant on-line 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.