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Radical-based neighboring segment matching method for on-line Chinese character recognition

机译:基于自由基的在线汉字识别相邻段匹配方法

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A new approach to stroke-order and stroke-number free on-line handwritten Chinese character recognition is presented in this paper. In this new scheme, the decision rule of the segment attribute is used to characterize the segment sequence appearing in each Chinese character for recognizing connected-stroke and even cursive handwritten Chinese characters. A knowledge-based radical extraction method is proposed to perform the feature extraction before radical recognition stage. The top-level and bottom-level radical classification are adopted in the coarse classification stage to reduce the number of candidate characters. In order to develop a stroke order free system, the neighboring segment matching method is proposed. Experimental results show that the proposed scheme is an efficient solution for stroke-order and stroke-number free on-line Chinese character recognition. The recognition rate is 93.4% and the recognition speed is 0.6 second per character.
机译:本文介绍了一种新的中风顺序和中风号码免费在线手写汉字识别。在此新方案中,段属性的决策规则用于表征出现在每个汉字中出现的段序列,以识别连接的笔划,甚至是Cursive手写汉字。提出了一种基于知识的自由基提取方法,以在自由基识别阶段进行特征提取。在粗略分类阶段采用顶级和底层自由基分类,以减少候选字符的数量。为了开发中风命令免费系统,提出了相邻的段匹配方法。实验结果表明,该方案是一种有效的行程顺序和中风号码在线汉字识别解决方案。识别率为93.4%,识别速度为0.6秒秒。

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