Paper Info
Title
On-line recognition of cursive Hangul characters by modeling extended graphemes
Abstract
We propose an effective method for online cursive Hangul recognition. Extended graphemes are modeled separately to recognize cursive characters, and rule processing is combined with elastic matching to discriminate similar characters. The extended graphemes consist of basic graphemes and connected graphemes of two or three basic graphemes which are frequently found in cursive Hangul characters. The rule based processing catches the specific features of graphemes whereas the elastic matching catches the general features of graphemes so the integration of two methods could complement the deficiencies of each other. In terms of integrating rules with elastic matching we could reduce 40.35% of error rates of grapheme recognition. The experiments produce 94.1% recognition rate for 479,326 Hangul characters (2350 different characters)
Year
DOI
Venue
1997
10.1109/ICDAR.1997.620574
ICDAR-1
Keywords
Field
DocType
cursive hangul character,cursive character,knowledge based systems,online cursive hangul recognition,connected grapheme,natural languages,extended grapheme,word processing,extended grapheme modeling,cursive hangul characters,rule processing,on-line recognition,grapheme recognition,error rates,basic grapheme,rule based processing,optical character recognition,recognition rate,elastic matching,hangul character,speech recognition,pattern matching,rule based,shape,pattern recognition,error rate
Elastic matching,Cursive,Rule-based system,Pattern recognition,Computer science,Grapheme,Optical character recognition,Speech recognition,Natural language,Artificial intelligence,Hangul,Word processing
Conference
Volume
ISSN
ISBN
2
1520-5363
0-8186-7898-4
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Kyung Hee Kim16817.89
Tae Jin Seong200.34
Jeong In Do300.34