Using skeleton and Hough transform variant to correct skew in historical documents

Omar Boudraa, Walid Khaled Hidouci and Dominique Michelucci

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 167, issue C, 389-403

Abstract: 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document analysis systems, Skew estimation represents one of the major research challenges, particularly in case of historical documents exploration.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).

Keywords: Skew estimation; Document image analysis; Skew correction; Progressive probabilistic Hough transform; Morphological skeleton (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:167:y:2020:i:c:p:389-403

DOI: 10.1016/j.matcom.2019.05.009

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