Abstract Stroke-order-free on-line Chinese character recognition by stroke adjustment of two-layer bipartite weighted matching
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Stroke-order-free on-line Chinese character recognition by stroke adjustment of two-layer bipartite weighted matching

机译:通过两层二部加权匹配的笔划调整实现无笔划在线汉字识别

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摘要

AbstractDynamic programming (DP) is good at recognizing on-line standard-stroke-order Chinese characters. We propose a two-stage bipartite weighted matching to rearrange the stroke order of a test on-line Chinese handwriting before recognition. At the first layer, for each stroke pair which matches one stroke in the test handwriting with one stroke in the reference character, we generate a stroke-based vector graph (SVG) and the bipartite weighted matching determines the best stroke permutation of the handwriting, stroke-based matched vector graph (SMVG), from the SVG. At the second layer, we superimpose all SMVGs to form a character-based vector graph (CVG), and the bipartite weighted matching calculates the final stroke mapping between the test handwriting and the reference character. Experimental results reveal that the modified split-and-merge DP matching using the stroke adjustment method recognizes on-line stroke-order-varied handwritings with accuracy 89%, much higher than accuracy 5.2% for the original split-and-merge DP matching.HighlightsDP is good at recognizing on-line standard-stroke-order Chinese characters.Bipartite matching for rearranging stroke order of an on-line Chinese handwriting.Modified split-and-merge DP matching for on-line stroke-order-varied handwritings.
机译: 摘要 动态编程(DP)擅长识别在线标准笔划顺序汉字。我们提出了一个两阶段两部分加权匹配,以在识别之前重新排列测试在线中文笔迹的笔划顺序。在第一层,对于与测试笔迹中的一个笔画与参考字符中的一个笔画相匹配的每个笔画对,我们生成一个基于笔画的矢量图(SVG),并且二分加权匹配确定了笔迹的最佳笔画排列,来自SVG的基于笔划的匹配矢量图(SMVG)。在第二层,我们将所有SMVG叠加在一起以形成基于字符的矢量图(CVG),然后通过二元加权匹配来计算测试笔迹和参考字符之间的最终笔划映射。实验结果表明,使用笔划调整方法的改进的拆分合并DP匹配可以识别在线笔划顺序变化的笔迹,其准确度为89%,远高于原始拆分合并DP匹配的准确度5.2%。 突出显示 < ce:list-item id =“ d1e376”> DP擅长识别在线标准笔划- 双向匹配,用于重新排列在线中文笔画的笔画顺序。 已修改的拆分合并DP匹配,用于在线笔顺顺序变化的笔迹。 / ce:para>

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