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A New Approach for Synthesis and Recognition of Large Scale Handwritten Chinese Words

机译:综合与识别大规模手写汉字的新方法

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Lacking of dataset is still a serious problem for researchers who study on online handwriting word recognition (HWR). In this paper, a handwritten Chinese word synthesis method is proposed for the first time to generate a large scale handwritten Chinese word dataset. The distributions of shape and position characteristics, such as aspect radio, character interval and the angle of gravity center line in each word sample of the Word8888 dataset have been estimated respectively. Based on this, we synthesize as large as 44,208 categories of 8,311,104 unconstrained handwritten Chinese word samples. To verify the validity of the synthesized dataset, a practical rotation free handwriting Chinese word recognition system is presented based on a new holistic approach. Experimental results for randomly rotated word samples demonstrate that the holistic approach can achieve 91.96% recognition accuracy, which provides evidence for the effectiveness of our method.
机译:缺乏数据集仍然是研究在线手写词识别(HWR)的研究人员的严重问题。在本文中,首次提出了一种手写的汉字综合方法来生成大规模手写中文词数据集。已经估计了SEATS和位置特性的分布和位置特性,例如宽视无线电,字符间隔和重心中心线在WORD8888数据集的每个字样中的重心。基于此,我们综合为44,208类8,311,104个不受约束的手写汉语单词样本。为了验证合成数据集的有效性,基于新的整体方法呈现了一个实际的旋转手写汉字识别系统。随机旋转的单词样本的实验结果表明整体方法可以达到91.96%的识别准确性,这为我们的方法提供了证据。

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