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    • 11. 发明授权
    • Character recognition system
    • 字符识别系统
    • US07254269B2
    • 2007-08-07
    • US10128773
    • 2002-04-19
    • Shinya Nakagawa
    • Shinya Nakagawa
    • G06K9/48
    • G06K9/6807
    • In the prior art, in character recognition of a language having many characters, such as Japanese, a feature vector is extracted from an input pattern, distances between the feature vector and reference vectors are calculated, and a character corresponding to a reference vector having the smallest distance value is selected as a recognized character. However, in the character recognition of a language having many characters, since the number of the reference vectors to be compared is large, there is a limit in improvement of processing speed of the character recognition. In the present invention, reference vectors corresponding to target characters are classified into plurality of classes based on occurrence frequencies of characters. When distances between the feature vector and the reference vectors are calculated, a comparison is sequentially made from the reference vectors of a class having a high character occurrence frequency, so that the processing speed of the character recognition is improved.
    • 在现有技术中,在诸如日语的具有许多字符的语言的字符识别中,从输入图案中提取特征向量,计算特征向量和参考向量之间的距离,并且对应于具有 选择最小距离值作为识别的字符。 然而,在具有许多字符的语言的字符识别中,由于要比较的参考向量的数量较大,因此在提高字符识别的处理速度方面存在限制。 在本发明中,对应于目标字符的参考矢量基于字符的出现频率被分类为多个等级。 当计算特征向量与参考矢量之间的距离时,从具有高字符出现频率的类的参考向量依次进行比较,从而提高了字符识别的处理速度。