Title :
On-line cursive Kanji character recognition using stroke-based affine transformation
Author :
Wakahara, Toru ; Odaka, Kazumi
Author_Institution :
NTT Human Interface Labs., Nippon Telegraph & Telephone Corp., Kanagawa, Japan
fDate :
12/1/1997 12:00:00 AM
Abstract :
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
Keywords :
character recognition; distortion-tolerant online cursive Kanji character recognition; handwriting distortion; stroke-based affine transformation; uniform affine transformation; Character recognition; Deformable models; Dynamic programming; Handwriting recognition; Keyboards; Natural languages; Nonlinear distortion; Pattern recognition; Shape; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
