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Classification and compression of digital newspaper images

机译:数字报纸图像的分类和压缩

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An improved scheme for newspaper block segmentation and classification is described. The newspaper image is first segmented into blocks using three passes of a run-length smoothing algorithm. Blocks may have any shape and need not be non-overlapped rectangles. The height H between the top-line and base-line of lower case letters, and the number of pixels that have values differing from their four neighboring pixels, are measured for simple and reliable block classification. Blocks of different types are compressed based on their own characteristics. Unlike conventional methods, halftone image blocks are treated differently from black and white graphic blocks for better compression. A lossless compression scheme for halftoned images is proposed. Reconstruction of gray-tones from halftone images employing information of both smooth and edgy areas is presented.
机译:描述了报纸块分割和分类的改进方案。首先使用运行长度平滑算法的三次通行证将报纸图像分段为块。块可能具有任何形状,并且不需要是非重叠矩形。针对简单可靠的块分类,测量小写字母的顶线和基线之间的高度H和具有与其四个相邻像素不同的值的像素的数量。基于自己的特性压缩不同类型的块。与传统方法不同,半色调图像块与黑白图形块不同地处理,以便更好地压缩。提出了半色调图像的无损压缩方案。介绍了从半色调图像中使用流畅和前卫区域信息的灰色音调重建。

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