Statistical mixture model for documents skew angle estimation

Amir Egozi, Its'Hak Dinstein

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish
Pages (from-to)1912-1921
Number of pages10
JournalPattern Recognition Letters
Issue number14
StatePublished - 15 Oct 2011


  • Expectation Maximization (EM)
  • Linear least squares
  • Skew detection
  • Statistical mixture models

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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