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Handwritten character recognition using elastic matching based on a category-dependent deformation model

机译:基于类别相关变形模型的弹性匹配手写字符识别

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摘要

For handwritten character recognition, a new elastic image matching (EM) technique based on a category-dependent deformation model is proposed. In the deformation model, any deformation of a category is described by a linear combination of eigen-deformations, which are intrinsic deformation directions of the category. The eigen-deformations can be estimated statistically from the actual deformations of handwritten characters. Experimental results show that the EM present technique can attain higher recognition rates than conventional EM techniques based on category-independent deformation models. The results also show the superiority of the present technique over those conventional EM techniques in computational efficiency.
机译:对于手写字符识别,提出了一种新的基于类别变形模型的弹性图像匹配(EM)技术。在变形模型中,类别的任何变形都通过特征变形的线性组合来描述,该特征变形是类别的固有变形方向。可以从手写字符的实际变形来统计估计本征变形。实验结果表明,与基于类别无关的变形模型的常规EM技术相比,EM当前技术可以获得更高的识别率。结果还显示了本技术在计算效率方面优于那些常规EM技术。

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