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

S. Uchida, H. Sakoe
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引用次数: 16

Abstract

For handwritten character recognition, a new elastic image matching (EM) technique based on a class-dependent deformation model is proposed. In the deformation model, any deformation of a class is described by a linear combination of eigen-deformations, which are intrinsic deformation directions of the class. The eigen-deformations can be estimated statistically from the actual deformations of handwritten characters. Experimental results show that the proposed technique can attain higher recognition rates than conventional EM techniques based on class-independent deformation models. The results also show the superiority of the proposed technique over those conventional EM techniques in computational efficiency.
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基于类相关变形模型的弹性匹配手写体字符识别
针对手写体字符识别,提出了一种基于类相关变形模型的弹性图像匹配技术。在变形模型中,类的任何变形都是由本征变形的线性组合来描述的,本征变形是类的本征变形方向。本征变形可以根据手写字符的实际变形进行统计估计。实验结果表明,该方法比基于类无关变形模型的传统电磁识别方法具有更高的识别率。结果还表明,该方法在计算效率上优于传统的电磁技术。
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