Segmentation of connected Chinese characters based on genetic algorithm
Segmentation of connected Chinese characters based on genetic algorithm
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DOI：
10.1109/icdar.2005.209
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发表时间：
2005-08
期刊：
影响因子：
--
通讯作者：
Xianghui Wei;Shaoping Ma;Yijiang Jin
中科院分区：
文献类型：
--
作者：
Xianghui Wei;Shaoping Ma;Yijiang Jin
汉字切分的准确性，尤其是连续汉字切分的准确性，是影响汉字识别系统性能的关键。提出了一种基于遗传算法的连续汉字切分方法。该算法将字符图像中间的一个固定区域定义为分割路径区（SPZ），通过遗传算法进化出最佳分割路径。初始种群由SPZ中的每一条点线组成。定义了个体编码、适应度函数、交叉算子和变异算子。实验结果表明，该方法在测试集上的平均正确率为88.9%，并且可以处理一些复杂类型的连续汉字，而不需要特殊的启发式规则。
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.