Segmentation of Connected Chinese Characters Based on Genetic Algorithm

Authors:
Xianghui Wei;Shaoping Ma;Yijiang Jin
Affiliations:
Institute of Software, CAS, China;CST Dept, Tsinghua Universit, China;CST Dept, Tsinghua Universit, China
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

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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.