DocumentCode :
311714
Title :
On-line cursive Kanji character recognition as stroke correspondence problem
Author :
Wakahara, Tom ; Suzuki, Akira ; Nakajima, Naoki ; Miyahara, Sueharu ; Odaka, Kazumi
Author_Institution :
NTT Human Interface Labs., Kanagawa, Japan
Volume :
2
fYear :
1995
fDate :
14-16 Aug 1995
Firstpage :
1059
Abstract :
This paper describes a stroke-number and stroke-order free on-line Kanji character recognition method by a joint use of two complementary algorithms of optimal stroke correspondence determination: one dissolves excessive mapping and the other dissolves deficient mapping. Also, three kinds of inter-stroke distances are devised to deal with stroke concatenation or splitting and heavy shape distortion. Only a single reference pattern for each of 2,980 Kanji character categories is generated by using training data composed of 120 patterns written with the correct stroke-number and stroke-order. Recognition tests are made using the training data and two kinds of resting data in the square style and in the cursive style written by 36 different people; recognition rates of 99.5%, 97.6%, and 94.1% are obtained
Keywords :
image segmentation; optical character recognition; complementary algorithms; deficient mapping; inter-stroke distances; online cursive Kanji character recognition; optimal stroke correspondence determination; single reference pattern; stroke concatenation; stroke correspondence problem; training data; Character generation; Character recognition; Dynamic programming; Handwriting recognition; Humans; Natural languages; Pattern matching; Shape; Testing; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
Type :
conf
DOI :
10.1109/ICDAR.1995.602091
Filename :
602091
Link To Document :
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