DocumentCode :
2173040
Title :
Recognizing on-line handwritten Chinese character via FARG matching
Author :
Zheng, Jing ; Ding, Xiaoqing ; Wu, Youshou
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Volume :
2
fYear :
1997
fDate :
18-20 Aug 1997
Firstpage :
621
Abstract :
The paper presents a novel method for online handwritten Chinese character recognition. In our method, each category of character is described by a fuzzy attributed relational graph (FARG). A relaxation algorithm is developed to match the input pattern with every FARG. For decision making, a similarity measure is established via statistical technique to calculate the matching degree between the input pattern and referenced FARG, according to which the recognition result is determined. The principle of our method makes it very robust against stroke connection and stroke order variation as well as stroke shape deformation. A database of 22530 samples collected from 6 subjects is used to test our recognition system which can recognize 3755 categories of Chinese characters. The result shows that our method is very effective: a top 1 recognition rate of 98.8% and a top 10 of 99.7% are reached
Keywords :
fuzzy set theory; graph theory; handwriting recognition; image matching; natural languages; statistical analysis; FARG matching; database; decision makin; fuzzy attributed relational graph; input pattern matching; online handwritten Chinese character recognition; recognition rate; recognition system; relaxation algorithm; similarity measure; statistical technique; stroke connection; stroke order variation; stroke shape deformation; Character recognition; Databases; Decision making; Handwriting recognition; Impedance matching; Pattern matching; Pattern recognition; Robustness; Shape; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
Type :
conf
DOI :
10.1109/ICDAR.1997.620578
Filename :
620578
Link To Document :
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