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A Phase Congruency Based Document Binarization

机译:基于相中的文档二值化

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In this paper, three new methods proposed for binarization of degraded documents and manuscripts. Phase congruency used to select regions of interest (ROI) of document's foreground. The main idea is to achieve an optimal recall measure (recall~1), while the precision value is at an acceptable level. Further processing should be performed to focus on the ROI. We also used a modified adaptive thresholding method in the next step. This method uses a global variance, a global mean and local means for thresholding. Finally, a new method called early exclusion criterion (EEC) proposed for document enhancement. The experimental results on the datasets introduced in DIBCO 2009, H-DIBCO 2010 and DIBCO 2011 shows that near optimal recall value (recall~0.99) obtained, while precision measure's value is acceptable.
机译:在本文中,提出了三种新方法,提出了劣化文件和手稿的二值化。用于选择文档前景的感兴趣区域(ROI)的相信。主要思想是实现最佳召回量度(召回〜1),而精度值处于可接受的水平。应执行进一步处理以专注于ROI。我们还在下一步骤中使用了修改的自适应阈值化方法。此方法使用全局方差,全局均值和本地方法用于阈值。最后,为文档增强提出了一种称为早期排除标准(EEC)的新方法。在DIBCO 2009中引入的数据集的实验结果,H-DIBCO 2010和DIBCO 2011示出了获得的近最佳召回值(召回〜0.99),而精确度量的值是可接受的。

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