An improved skew angle detection and correction technique for historical scanned documents using morphological skeleton and progressive probabilistic hough transform

Skew detection is a crucial step for document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust skew angle detection and correction technique. Morphological Skeleton is introduced to sign...

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Bibliographic Details
Published in:2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B) pp. 1 - 6
Main Authors: Boudraa, Omar, Hidouci, Walid Khaled, Michelucci, Dominique
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2017
Subjects:
Document image analysis
Electronic mail
Histograms
Morphological Skeleton
Probabilistic logic
Progressive Probabilistic Hough Transform
Robustness
Skeleton
Skew angle detection
Skew correction
Text analysis
Transforms
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Summary:Skew detection is a crucial step for document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust skew angle detection and correction technique. Morphological Skeleton is introduced to significantly reduce the amount of data to treat by removing the redundant pixels and keeping only the central curves of the image components. The proposed method then uses Progressive Probabilistic Hough Transform (PPHT) to identify image lines. A special procedure is finally applied in order to estimate the global skew angle of the document image from these detected lines. Experimental results prove the accuracy and the efficiency of our approach on skew angle detection over three popular datasets containing various types of document of different linguistic writings (such as Chinese, English and Greek) and diverse styles (multi-columns, with figures and tables, vertical or horizontal orientations).
DOI:10.1109/ICEE-B.2017.8192043