摘要：

分析汉字结构特征及其演变，在汉字字库及汉字识别目标变化的基础上，结合汉字识别过程，研究与比较贝叶斯决策、二次判别函数法、隐马尔科夫模型、神经网络分类器以及支持向量机这5种汉字识别方法的优缺点及适用范围。结果表明，汉字识别方法仍需要在识别目标及特征提取、训练字符集准备方面进行改进。

关键词: 汉字识别, 模式识别, 贝叶斯决策, 多分类器聚合, 分类识别

Abstract:

This paper analyzes Chinese character structure feature and evolution, combines the character recognition process together on the basis of Chinese character database and changing in recognition target, researches and comprises the advantages, disadvantages and the application range of five different kinds of Classification recognition method such as Bayesian method, quadratic discriminate function approach, Markov model, neural network classifier and Support Vector Machine(SVM). Results shows that Chinese character recognition method including recognition should be improved on the aspects of target, feature extracting and train set preparing.

Key words: Chinese character recognition, pattern recognition, Bayesian decision, multiple classifier polymerization, classification recognition

中图分类号: 

• TP393