Skew estimation of document images using bagging

Authors:
Gaofeng Meng;Chunhong Pan;Nanning Zheng;Chen Sun
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing and Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, C ...;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China;Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China
Venue:
IEEE Transactions on Image Processing
Year:
2010

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Abstract

This paper proposes a general-purpose method for estimating the skew angles of document images. Rather than to derive a skew angle merely from text lines, the proposed method exploits various types of visual cues of image skew available in local image regions. The visual cues are extracted by Radon transform and then outliers of them are iteratively rejected through a floating cascade. A bagging (bootstrap aggregating) estimator is finally employed to combine the estimations on the local image blocks. Our experimental results show significant improvements against the state-of-the-art methods, in terms of execution speed and estimation accuracy, as well as the robustness to short and sparse text lines, multiple different skews and the presence of nontextual objects of various types and quantities.