Global Skew Detection and Correction Using Morphological and Statistical Methods

  • Sharfuddin Waseem MohammedEmail author
  • Narasimha Reddy Soora
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)


In this paper we have proposed a technique for skew detection and correction for printed documents, and have used an existing Optical Character Recognition (OCR) to recognize the characters. The proposed algorithm has the following steps (a) Applying the morphological dilations by defining the various structure elements (SE) (b) extracting the longest connected components (CC) (c) finding the global skew angle by statistical analysis of connected component (d) reference text line estimation and regression line fit to rotate the individual line by estimated angle of rotation. We have conducted experiment using printed images having different languages i.e. English, Devanagari, and Arabic (custom dataset) and have achieved significant performance.


Morphological dilations Statistical analysis Regression line fit Connected components analysis 


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Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  • Sharfuddin Waseem Mohammed
    • 1
    Email author
  • Narasimha Reddy Soora
    • 1
  1. 1.Department of Computer Science and EngineeringKakatiya Institute of Technology and SciencesWarangalIndia

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