Skew estimation and correction for form documents using wavelet decomposition

Authors:
Dihua Xi;Mohamed Kamel;Seong-Whan Lee
Affiliations:
Pattern Analysis and Machine Intelligence Research Group, Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada;Pattern Analysis and Machine Intelligence Research Group, Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada;Center for Artificial Vision Research, Korea University, Seoul, Korea
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

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Abstract

Form document image processing has become an increasingly essential technology in office automation tasks. One of the problems is that the document image may appear skewed for many reasons. Therefore, the skew estimation plays an important role in any automatic document analysis system. In the past few years, many algorithms have been developed to detect the skew angle of text document images. However, these algorithms suffer from two major deficiencies. Firstly, most of them suppose that the original image is monochrome and therefore they are not suitable to apply to documents with a complicated background. Secondly, most of the current methods were developed for general document images that are not as complicated as form documents. In this paper, we present a new approach to skew detection for grey-level form document images. In our system, image decomposition by 2D wavelet transformations is used to estimate the skew angle.