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Skew detection and correction in document images based on straight-line fitting

机译:基于直线拟合的文档图像歪斜检测和校正

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摘要

During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithms for layout analysis and character recognition are generally very sensitive to the page skew, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method based on straight-line fitting is proposed. And a concept of eigen-point is introduced. After the relations between the successive eigen-points in every text line within a suitable sub-region were analyzed, the eigen-points most possibly laid on the baselines are selected as samples for the straight-line fitting. The average of these baseline directions is computed, which corresponds to the degree of skew of the whole document image. Then a fast skew correction method based on the scanning line model is also presented. Experiments prove that the proposed approaches are fast and accurate.
机译:在文档扫描期间,歪斜不可避免地会引入到传入的文档图像中。由于用于布局分析和字符识别的算法通常对页面倾斜非常敏感,因此文档图像中的倾斜检测和校正是布局分析之前的关键步骤。提出了一种基于直线拟合的偏斜检测新方法。并引入了本征点的概念。在分析了合适子区域中每个文本行中连续特征点之间的关系之后,选择最有可能置于基线上的特征点作为直线拟合的样本。计算这些基线方向的平均值,它对应于整个文档图像的歪斜度。然后提出了一种基于扫描线模型的快速偏斜校正方法。实验证明,该方法是快速,准确的。

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