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Stroke-Based Character Segmentation of Low-Quality Images on Ancient Chinese Tablet

机译:基于笔划的古代汉字平板低质量图像字符分割

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Ancient Chinese tablets are invaluable in terms of historical and aesthetic value. Automatic character segmentation of images from degraded tablets poses a challenging problem. Therefore, this paper proposes a new character segmentation method that utilizes an enhanced stroke filter and an energy propagation process based on local layout information. A ground-truth dataset was established to evaluate the accuracy of the algorithm adopted by the proposed segmentation method. Experimental results indicate that the proposed method can effectively extract characters from low-quality ancient Chinese tablet images.
机译:就历史和美学价值而言,中国古代碑牌是无价的。来自降解药片的图像的自动字符分割提出了一个具有挑战性的问题。因此,本文提出了一种新的字符分割方法,该方法利用了增强的笔触过滤器和基于局部布局信息的能量传播过程。建立了一个真实的数据集,以评估所提出的分割方法所采用算法的准确性。实验结果表明,该方法可以有效地从低质量的中国古代平板图像中提取字符。

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