首页> 外文会议>Proceedings of the 2006 International Conference on Machine Learning and Cybernetics >LEARNING PATTERN GENERATION FOR HANDWRITTEN CHINESE CHARACTER USING PATTERN TRANSFORM METHOD WITH COSINE FUNCTION
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LEARNING PATTERN GENERATION FOR HANDWRITTEN CHINESE CHARACTER USING PATTERN TRANSFORM METHOD WITH COSINE FUNCTION

机译:利用余弦函数的图形变换方法生成手写汉字的学习图形

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In pattern recognition, the number and quality of learning patterns is of crucial importance. When the number and quality of learning patterns are limited, error occurs in the presumed distribution of patterns and the precision of whole recognition system decreases. In this paper, a new pattern generation method is proposed which contributes to improvement of the performance of a handwritten Chinese character recognition system. By using this pattern generation technique, we increase the number and quality of learning patterns by using transform method with cosine function.Patterns generated this way are then selected using pattern selection method and the patterns unsuitable for learning are discarded. The recognition experiment on HCL2000, a handwritten Chinese character database, shows that our method improves the recognition precision of whole system.
机译:在模式识别中,学习模式的数量和质量至关重要。当学习模式的数量和质量受到限制时,假定的模式分布会发生错误,并且整个识别系统的精度会降低。本文提出了一种新的模式生成方法,该方法有助于提高手写汉字识别系统的性能。通过使用这种模式生成技术,我们通过使用具有余弦函数的变换方法来增加学习模式的数量和质量,然后使用模式选择方法选择以此方式生成的模式,并丢弃不适合学习的模式。在手写汉字数据库HCL2000上的识别实验表明,该方法提高了整个系统的识别精度。

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