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A Recognition Algorithm for Chinese Character Based on minimum Distance Classifier

机译:基于最小距离分类器的汉字识别算法

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This paper investigates problems of image character recognition, especially Chinese character recognition. We herein recommend a novel recognition algorithm which is based on minimum distance classifier. Aiming at a subset of the features in a character that a human can typically see for the identification of typewritten Chinese characters, the algorithm attempts to work with two classes of feature extraction-structure and statistics. The statistic feature decides the primary class and the structure feature is used to identify Chinese characters. This paper also describes, analyzes and compares several other methods and results. Experimental results indicate that the recognition algorithm is effective for Chinese character in image.
机译:本文调查了图像字符识别,尤其是汉字识别的问题。我们在此建议一种基于最小距离分类器的新颖识别算法。针对人类通常可以看到识别打字汉字的特征的子集,该算法尝试使用两类特征提取结构和统计数据。统计功能决定主类,结构功能用于识别汉字。本文还描述了分析和比较了其他几种方法和结果。实验结果表明,识别算法对图像中的汉字是有效的。

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