DocumentCode :
1213508
Title :
Knowledge model based approach in recognition of on-line Chinese characters
Author :
Chou, Kuo-Sen ; Fan, Kuo-Chin ; Fan, Tzu-I ; Lin, Chang-Keng ; Jeng, Bor-Shenn
Volume :
12
Issue :
9
fYear :
1994
fDate :
12/1/1994 12:00:00 AM
Firstpage :
1566
Lastpage :
1575
Abstract :
A knowledge model-based OCR system is presented for the recognition of on-line connected stroke Chinese characters. In the approach, segment attributes are first extracted to characterize the segment sequence of an unknown character. Next, radical recognition based on model matching is adopted as the coarse classification to reduce the number of candidate characters before detailed matching. Finally, a deviation modeling method is proposed to recognize not only regular writing characters but also characters with stroke-order and stroke-number deviations. The effectiveness of the approach is verified by experiments on the recognition of on-line Chinese characters
Keywords :
image classification; image matching; knowledge based systems; optical character recognition; tree searching; OCR system; coarse classification; connected stroke Chinese characters; deviation modeling method; knowledge model based approach; model matching; online Chinese characters; radical recognition; recognition; regular writing characters; segment attribute; segment sequence; stroke-number deviations; stroke-order deviations; Character recognition; Computer science; Dynamic programming; Helium; Laboratories; Office automation; Optical character recognition software; User interfaces; Writing;
fLanguage :
English
Journal_Title :
Selected Areas in Communications, IEEE Journal on
Publisher :
ieee
ISSN :
0733-8716
Type :
jour
DOI :
10.1109/49.339925
Filename :
339925
Link To Document :
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