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A Stroke-Density Based Double Elastic Meshing Feature Extraction Method for Chinese Handwritten Character Recognition

机译:基于笔划密度的双弹性网格特征提取方法在中文手写字符识别中的应用

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Stroke-density based elastic meshing method can not only absorb the deformations of stroke in different handwritings but also avoid the non-uniform width of strokes which caused by using a nonlinear normalization method. In view of existing situation that the stroke density functions do not consider the distribution of strokes in diagonal direction, the stroke-density based vertical-horizontal elastic meshing method could not effectively extract the feature of left-falling and right-falling stroke in a Chinese handwritten character image, we propose a new stroke density definition of a diagonal direction and combine it with diagonal elastic meshing technique to constitute meshes. Then, combining the vertical-horizontal elastic meshes with the diagonal's, we get the stroke-density based double elastic meshing approach. The experimental results have verified the effectiveness of this method.
机译:基于笔划密度的弹性网格划分方法不仅可以吸收笔迹在不同笔迹中的变形,而且可以避免由于非线性归一化方法而导致笔划宽度的不均匀性。鉴于笔划密度函数不考虑笔划在对角线方向上的分布的现状,基于笔划密度的垂直-水平弹性网格划分方法无法有效地提取汉字中左,右落笔划的特征。在手写字符图像中,我们提出了对角线方向的新笔划密度定义,并将其与对角线弹性网格划分技术相结合以构成网格。然后,结合垂直和水平的弹性网格与对角线的网格,我们得到了基于笔划密度的双重弹性网格方法。实验结果证明了该方法的有效性。

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