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基于多通道PCA模型的手写汉字识别方法

DOI: 10.11834/jig.200307276

Keywords: 多通道PCA模型,手写汉字识别,主分量分析,欧氏距离分类器

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Abstract:

为了提高手写汉字的识别率和降低训练时间,提出了一种基于多通道PCA(Principalcomponentanalysis)模型的手写汉字识别方法.该方法首先根据汉字的结构特点,将手写汉字分解为“一”、“I”、“J”、“\”4种方向子模式,然后分别对每个子模式进行主分量分析,最后通过建立起每类汉字的多通道PCA模型来进行手写汉字的识别.该方法既兼顾了主分量对手写汉字的描述能力,又有效地降低了建立模型的训练时间.针对1034类别的手写汉字样本的实验结果表明,该汉字识别方法的识别率较欧氏距离分类器提高了4.4个百分点,而其训练时间则明显低于直接进行PCA重建的识别方法,由此可见,该方法是有效的。

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