介绍一种采用可能性理论与模糊逻辑方法相结合的自动学习分类器设计系统。该系统通过学习抽样字符可测定特征值的可能性。分类器利用模糊逻辑来联合几种特征而计算出全特征组的可能性。在分类器设计中可以自由选择字符类及特征的数量。所描述的印刷体汉字识别包括粗分类及两级精分类。为了克服字符结构变化对特征的影响，在字符点阵中将特征抽取区域的界线模糊化。全系统包括字体分类器及四个单字体分类器。
A method using possibility theory and fuzzy logic is introduced. Possibility functions of each feature are determined during training. Methods of fuzzy logic are used to combine the possibility of different features. This Chinese character recognition system consists of a pre-classifier and a two-level fine classifier. In order to handle deviations of the characters,a fuzzification of features is introduced. This method is used to develop single-font classifiers. The whole system consists of a font-classifiers and four single-font-classifiers.
米福 张平.一种自动学习的印刷体汉字识别系统[J].重庆大学学报,1996,19(1):40-45.
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