DocumentCode :
3021446
Title :
Segmentation of connected Chinese characters based on genetic algorithm
Author :
Wei, Xianghui ; Ma, Shaoping ; Jin, Yijiang
Author_Institution :
Inst. of Software, Chinese Acad. of Sci., China
fYear :
2005
fDate :
29 Aug.-1 Sept. 2005
Firstpage :
645
Abstract :
The accuracy of segmenting Chinese character, especially connected Chinese characters, is essential for the performance of a Chinese character recognition system. In this paper, a new approach for segmenting connected Chinese characters based on genetic algorithm is proposed. The best segmentation path is evolved by genetic algorithm from a fixed area located in the middle of character image which is defined as segmentation path zone (SPZ). The initial population is composed of each point line in SPZ. The individual coding, fitness function, crossover operator and mutation operator are also defined for this task. Experimental results on a dataset extracted from the four vaults show that our approach can get an average accuracy of 88.9% on test set and can handle some complex types of connected Chinese characters without special heuristic rules.
Keywords :
character recognition; genetic algorithms; image segmentation; Chinese character recognition system; character segmentation; crossover operator; fitness function; genetic algorithm; mutation operator; segmentation path zone; Character recognition; Content addressable storage; Genetic algorithms; Genetic mutations; Image segmentation; Optical character recognition software; Skeleton; Software performance; Testing; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN :
1520-5263
Print_ISBN :
0-7695-2420-6
Type :
conf
DOI :
10.1109/ICDAR.2005.209
Filename :
1575624
Link To Document :
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