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Textured reductions for document image analysis

机译:用于文档图像分析的纹理化还原

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Abstract: A particularly effective method for analyzing document images, that consist of large numbers of binary pixels, is to generate reduced images whose pixels represent enhancements of textural densities in the full-resolution image. These reduced images are generated using an integrated combination of filtering and subsampling. Previously reported methods used thresholding over a square grid, and cascaded these threshold reduction operations. Here, the approach is generalized to a sequence of arbitrary filtering/subsample operations, with emphasis on several particular filtering operations that respond to salient textural qualities of document images, such as halftones, lines or blocks of text, and horizontal or vertical rules. As with threshold reductions, these generalized 'textured reductions' are performed with no regard for connected components. Consequently, the results are typically robust to noise processes that can vitiate analysis based on connected components. Examples of image analysis and segmentation operations using textured reductions are given. Some properties can be determined very quickly; for example, the existence or absence of halftone regions in a full page image can be established in about 10 milliseconds. !11
机译:摘要:一种由大量二进制像素组成的分析文档图像的特别有效的方法是生成缩小的图像,其像素代表全分辨率图像中纹理密度的增强。这些缩小的图像是使用滤波和二次采样的集成组合生成的。先前报道的方法在正方形网格上使用阈值化,并将这些阈值降低操作级联。在这里,该方法被概括为一系列任意过滤/子采样操作,重点是对文档图像的显着纹理质量(例如半色调,文本的行或块以及水平或垂直的规则)做出响应的几种特定的过滤操作。与阈值减少一样,这些广义的“纹理化减少”是在不考虑连接组件的情况下执行的。因此,结果通常对噪声处理具有鲁棒性,该噪声处理可以使基于连接的组件的分析无效。给出了使用纹理缩小的图像分析和分割操作的示例。可以很快确定某些属性。例如,可以在大约10毫秒内确定整页图像中是否存在半色调区域。 !11

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