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

Authors:
Yang Cao;Shuhua Wang;Heng Li
Affiliations:
Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, PR China;Department of Computer Science and Technology, Nanjing University, Nanjing, PR China;Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong, PR China
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

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.