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An improved contour-based thinning method for character images

机译:一种改进的基于轮廓的字符图像细化方法

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摘要

Digital skeleton of character images, generated by thinning method, has a wide range of applications for shape analysis and classification. But thinning of character images is a big challenge. Removal of spurious strokes or deformities in thinning is a difficult problem. In this paper, we propose a contour-based thinning method used for performing skeletonization of printed noisy isolated character images. In this method, we use shape characteristics of text to get skeleton of nearly same as the true character shape. This approach helps to preserve the local features and true shapes of the character images. As a by-product of our thinning approach, the skeleton also gets segmented into strokes in vector form. Hence further stroke segmentation is not required. Experiment is done on printed English, Bengali, Hindi, and Tamil characters and we obtain much better results comparing with other thinning methods without any post-processing.
机译:通过细化方法生成的字符图像的数字骨架,在形状分析和分类中具有广泛的应用。但是字符图像的细化是一个很大的挑战。消除变薄中的虚假笔划或变形是一个难题。在本文中,我们提出了一种基于轮廓的细化方法,用于对打印的带噪孤立字符图像进行骨架化。在这种方法中,我们使用文本的形状特征来获得与真实字符形状几乎相同的骨架。这种方法有助于保留字符图像的局部特征和真实形状。作为我们的细化方法的副产品,骨骼也被分割成矢量形式的笔触。因此,不需要进一步的笔划分割。实验是对印刷的英语,孟加拉语,北印度语和泰米尔语字符进行的,与没有任何后处理的其他细化方法相比,我们获得了更好的结果。

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