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Super-Resolved Binarization of Text Based on the FAIR Algorithm

机译:基于FAIR算法的文本超分辨二值化

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In this paper, we present a novel approach for super-resolved binarization of document images acquired by low quality devices. The algorithm tries to compute the super resolution of the likelihood of text instead of the gray value of pixels. This method is the extension of a binarization algorithm (FAIR: a Fast Algorithm for document Image Restoration) which has been submitted into different contests where it showed good performances. The method can be considered as parameter free and is based on a rough localization of text in order to save computation time. Experimental results on several image sequences presenting a background noise and variation in contrast and illumination show the effectiveness of the method.
机译:在本文中,我们提出了一种新方法,用于对由低质量设备获取的文档图像进行超分辨二值化。该算法尝试计算文本似然性的超分辨率,而不是像素的灰度值。此方法是二值化算法(FAIR:用于文档图像恢复的快速算法)的扩展,该算法已提交到表现出良好性能的不同比赛中。该方法可以被认为是无参数的,并且基于文本的粗略本地化以节省计算时间。在呈现背景噪声以及对比度和照明变化的几个图像序列上的实验结果表明了该方法的有效性。

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