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A modified thinning strategy to handle junction point distortion for Bangla characters

机译:一种改进的细化策略,可处理孟加拉字符的交点变形

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Thinning which is an important preprocessing step for character recognition is often subject to several kinds of distortion. Junction point distortion is a major imperfection in thinned images especially for handwritten Indian scripts due to the presence of large number of complicated junctions in them. Such distortion does allow the optical character recognition (OCR) systems to exploit the properties of these junctions for character recognition. We present a novel methodology to reduce distortion at junction regions adjoining the matra for BangIa script. Our method uses geometric properties of the junctions to solve the problem. We have tested our approach on our own data set consisting of a variety of isolated handwritten character images by different writers and have got promising results.
机译:细化是字符识别的重要预处理步骤,通常会受到多种失真的影响。交点失真是稀化图像中的主要缺陷,特别是对于手写的印度文字而言,因为其中存在大量复杂的交点。这种失真确实允许光学字符识别(OCR)系统利用这些结的特性进行字符识别。我们提出了一种新颖的方法来减少BangIa脚本在与Matra相邻的交界处的变形。我们的方法使用结点的几何特性来解决该问题。我们已经在我们自己的数据集上测试了我们的方法,该数据集由不同作者编写的各种孤立的手写字符图像组成,并取得了可喜的结果。

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