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Proceedings Paper

A progressive de-skewing technique for document image analysis
Author(s): James Haralambides; Dimitrios Charalampidis
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Paper Abstract

Skew detection in document images is an important pre-processing step for several document analysis algorithms. In this work, we propose a fast method that estimates skew angles based on a local-to-global approach. Many existing techniques that are based on connected component analysis, group together pixels in order to form small document objects. Then, a Hough transform is used to estimate the skew angle. The connected components detection process introduces an undesired overhead. Nearest neighbor based techniques are only based on local groups and thus fail to achieve great skew accuracy. Techniques based on projections create 1-D profiles by successively rotating the document in a range of angles. The detection speed can be accelerated considering rotations from coarse to fine. However, the rotation and projection can be relatively slow. The proposed technique is characterized by both high processing speed and high skew estimation accuracy. First, local ring-shaped areas are analyzed for an initial skew estimation by building angle histograms between random points and the ring centers. Following a ring selection process, a single histogram is obtained. A range of angles around the best candidates obtained from the initial skew estimation is further examined. Experimental results have shown that the proposed technique yields superior results in terms of estimation accuracy and speed compared to existing techniques.

Paper Details

Date Published: 25 April 2007
PDF: 12 pages
Proc. SPIE 6575, Visual Information Processing XVI, 657504 (25 April 2007); doi: 10.1117/12.720128
Show Author Affiliations
James Haralambides, Barry Univ. (United States)
Dimitrios Charalampidis, Univ. of New Orleans (United States)


Published in SPIE Proceedings Vol. 6575:
Visual Information Processing XVI
Zia-ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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