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Robust skew estimation using straight lines in document images

机译:使用文档图像中的直线进行可靠的偏斜估计

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A skew-estimation method using straight lines in document images is presented. Unlike conventional approaches exploiting the properties of text, we formulate the skew-estimation problem as an estimation task using straight lines in images and focus on robust and accurate line detection. To be precise, we adopt a block-based edge detector followed by a progressive line detector to take clues from a variety of sources such as text lines, boundaries of figures/tables, vertical/horizontal separators, and boundaries of textblocks. Extensive experiments on the datasets of skewed images and competition results reveal that the proposed method works robustly and yields accurate skew-estimation results. (C) 2016 SPIE and IS&T
机译:提出了一种在文档图像中使用直线的偏斜估计方法。与利用文本属性的传统方法不同,我们将歪斜估计问题公式化为使用图像中的直线的估计任务,并着重于鲁棒和准确的线条检测。确切地说,我们采用基于块的边缘检测器,然后采用逐行检测器,以从各种来源中获取线索,例如文本行,图形/表格的边界,垂直/水平分隔符和文本块的边界。对偏斜图像和竞争结果的数据集进行的大量实验表明,该方法具有很好的鲁棒性,并且可以产生准确的偏斜估计结果。 (C)2016 SPIE和IS&T

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