Statistical mixture model for documents skew angle estimation

Authors:
Amir Egozi;Its'hak Dinstein
Affiliations:
Ben-Gurion University of the Negev, Electrical and Computer Engineering Department, Beer-Sheva 84105, Israel;Ben-Gurion University of the Negev, Electrical and Computer Engineering Department, Beer-Sheva 84105, Israel
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

We present a statistical approach to skew detection, where the distribution of textual features of document images is modeled as a mixture of straight lines in Gaussian noise. The Expectation Maximization (EM) algorithm is used to estimate the parameters of the statistical model and the estimated skew angle is extracted from the estimated parameters. Experiments demonstrate that our method is favorably comparable to other existing methods in terms of accuracy and efficiency.