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An efficient binarization method for ancient Mongolian document images

机译:一种有效的古代蒙古文献图像二值化方法

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In order to recognize and retrieve the Mongolian Kanjur images, lots of preprocessing tasks should be done. In this paper, we concentrate on the binarization of the Mongolian Kanjur images and we have proposed an efficient binarization method for them. The proposed method is applied to each image as follows: First, some preprocessing tasks including grayscaling and smoothing are executed. Second, three well-known global thresholding methods are used for extracting regions of interest (ROIs) from every gray-level image. Then, each ROI is processed by a modified Sauvola's algorithm with variant sizes of the small windows. Experimental results have proved that the proposed binarization method is better than the original Sauvola's algorithm.
机译:为了识别和检索蒙古语Kanjur图像,应完成许多预处理任务。在本文中,我们集中于蒙古语Kanjur图像的二值化,并为它们提出了一种有效的二值化方法。所提出的方法应用于每个图像,如下所示:首先,执行一些预处理任务,包括灰度和平滑。第二,使用三种众所周知的全局阈值方法从每个灰度图像中提取感兴趣区域(ROI)。然后,通过修改后的Sauvola算法处理小窗口大小可变的每个ROI。实验结果证明,提出的二值化方法优于原始的Sauvola算法。

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