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Reseach Article

An approach for Skew Detection using Hough Transform

by Bhavesh Kumar Shukla, Gautam Kumar, Ashish Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 9
Year of Publication: 2016
Authors: Bhavesh Kumar Shukla, Gautam Kumar, Ashish Kumar
10.5120/ijca2016908567

Bhavesh Kumar Shukla, Gautam Kumar, Ashish Kumar . An approach for Skew Detection using Hough Transform. International Journal of Computer Applications. 136, 9 ( February 2016), 20-23. DOI=10.5120/ijca2016908567

@article{ 10.5120/ijca2016908567,
author = { Bhavesh Kumar Shukla, Gautam Kumar, Ashish Kumar },
title = { An approach for Skew Detection using Hough Transform },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 9 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 20-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number9/24182-2016908567/ },
doi = { 10.5120/ijca2016908567 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:38.893151+05:30
%A Bhavesh Kumar Shukla
%A Gautam Kumar
%A Ashish Kumar
%T An approach for Skew Detection using Hough Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 9
%P 20-23
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Detecting skew of any document image and correcting that are important issues in the preprocessing stage of OCR system. The Hough Transform is a technique that performs skew detection in the document images. In the present work, voting is done on the basis of angle from 0 to less than 90°. Moving from one angle say ϴ1 to Ө2 , five partitioned are considered i.e. there would be 450 classes. Voting is the process to find the belongingness of a pixel to a particular class. Finally, each pixel present in skewed image is found to which class it belongs. The class which has maximum count of the pixels is taken as skewed angle class.Performance of our algorithm is analysed. It gives increasing results.

References
  1. C. Singh, N. Bhatia and A. Kaur, “Hough transform based fast skew detection and accurate skew correction methods”, Pattern Recognition, vol.41, pp.3528-3546, 2008.
  2. R. O. Duda and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Comm. ACM, vol. 15, pp. 11–15, January 1972.
  3. A Amin and S. Fischer, “A Document Skew Detection Method Using the Hough Transform”, Pattern Analysis & Applications, vol. 3, pp. 243-253, 2000.
  4. N.V.A. Manjunath, G.H. Hemantha , and P. Shivakumara , “Skew Detection Technique for Binary Document Images based on Hough Transform”, International Journal of Information Technology, vol.3, no. 3, pp. 194-200, 2006
  5. M. Ahmed and R. Ward, “A Rotation Invariant rule-Based Thinning Algorithm for Character Recognition”, IEEE Transaction on pattern analysis and machine Intelligence, vol. 24, no. 12, December 2002.
  6. H.S. Baird, “Anatomy of a versatile page reader”, Proceedings of the IEEE, vol.80, no.7, pp.1059–1065, 1992.
  7. S.C. Hinds, J.L. Fisher and D.P. D’Amato, “A Document Skew Detection Method Using Run-Length Encoding and The Hough Transform”, Proceedings 10th International Conference On Pattern Recognition, pp. 464–468, 1990.
  8. S. N. Srihari and V. Govindaraju,“Analysis of textual images using the Hough Transform”, Machine Vision and Applications,vol. 2, pp. 141-153, 1989.
  9. D. S. Le, G. R. Thoma and H. Wechsler, “Automated page orientation and skew angle detection for binary document images”,Pattern Recognition, vol. 27, no. 10, pp.1325-1344, 1994.
  10. Y. Ishitani, “Document skew detection based on local region complexity”, Proceedings of the Second IEEE International Conference onDocumenta analysis and recognition, vol. 7 pp:49–52, 1993
  11. A. Hashizume, P-S Yeh and A. Rosenfeld,“A method of detecting the orientation of aligned components”, Pattern Recognition Letters, vol. 4, pp. 125-132, 1986.
Index Terms

Computer Science
Information Sciences

Keywords

Skew detection Hough Transform OCR