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Using skeleton and Hough transform variant to correct skew in historical documents

机译:使用骨架和霍夫变换变形来纠正历史文档中的偏斜

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As a main part of several document analysis systems, Skew estimation represents one of the major research challenges, particularly in case of historical documents exploration. In this paper, we propose an original skew angle detection and correction technique. Morphological Skeleton is introduced to considerably diminish the amount of data by eliminating the redundant pixels and preserving only the central curves of the image components. Next, the proposed method uses Progressive Probabilistic Hough Transform (PPHT) to find image lines. At the end, a specific procedure is applied in order to measure the global skew angle of the document image from these identified lines. Experimental results demonstrate the accuracy and the effectiveness of our approach on skew angle detection upon three popular datasets covering many types of documents of diverse linguistic writings (Chinese, Greek and English) and different styles (horizontal or vertical orientations, including figures and tables, multi-columns page layouts). (C) 2019 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
机译:作为几种文件分析系统的主要部分,偏斜估计代表了主要的研究挑战之一,特别是在历史文件探索的情况下。在本文中,我们提出了一种原始的偏斜角检测和校正技术。通过消除多余像素并仅保留图像分量的中心曲线,引入了“形态学骨架”以大大减少数据量。接下来,提出的方法使用渐进概率霍夫变换(PPHT)查找图像线。最后,为了从这些识别的行中测量文档图像的整体歪斜角,将应用特定的过程。实验结果证明了我们的偏斜角检测方法的正确性和有效性,该方法基于三个流行的数据集,涵盖了多种语言文字(中文,希腊语和英语)和不同样式(水平或垂直方向,包括图形和表格)的多种类型的文档。 -列页面布局)。 (C)2019国际模拟数学与计算机协会(IMACS)。由Elsevier B.V.发布。保留所有权利。

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