CFP last date
22 April 2024
Reseach Article

Robust Document Image Binarization Technique for Degraded Document Images by using Morphological Operators

Published on September 2016 by Rupinder Kaur, Naveen Kumar
International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2016 - Number 8
September 2016
Authors: Rupinder Kaur, Naveen Kumar
b1564d96-6729-48a3-82d7-7dbfcb925b77

Rupinder Kaur, Naveen Kumar . Robust Document Image Binarization Technique for Degraded Document Images by using Morphological Operators. International Conference on Advances in Emerging Technology. ICAET2016, 8 (September 2016), 11-15.

@article{
author = { Rupinder Kaur, Naveen Kumar },
title = { Robust Document Image Binarization Technique for Degraded Document Images by using Morphological Operators },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { September 2016 },
volume = { ICAET2016 },
number = { 8 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 11-15 },
numpages = 5,
url = { /proceedings/icaet2016/number8/25925-t121/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Rupinder Kaur
%A Naveen Kumar
%T Robust Document Image Binarization Technique for Degraded Document Images by using Morphological Operators
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2016
%N 8
%P 11-15
%D 2016
%I International Journal of Computer Applications
Abstract

To make a robust document images from badly degraded images it is necessary to discriminating a text from background images but it is a very challenging task. There are so many binarization techniques can be used for making the document pictures reliable. But problem of thresholding and filtering cannot be solved. In the existing method, edge based segmentation can be done and Canny edge detector used. In our proposed technique, Image Binarzation for degraded document images has being use Region based segmentation. Firstly, an RGB image convert into gray image then image filtering can be done on the basis of Wiener Filtering and Gaussian filter. In the proposed method, we can modify algorithms and test degraded document images then compare the result that come from previous paper results.

References
  1. George Nagy, "Twenty years of document image analysis in PAMI," IEEE Transactions on Pattern Analysis and Machine Intelligence22. 1, pp. 38-62, 2000.
  2. David L. , et al. Milgram, Algorithms and hardware technology for image recognition. : MARYLAND UNIV COLLEGE PARK COMPUTER SCIENCE CENTER, 1978.
  3. Ioannis Pratikakis, and Stavros J. Perantonis. Gatos Basilios, "Improved document image binarization by using a combination of multiple binarization techniques and adapted edge information," , 2008.
  4. and Fatos T. Yarman-Vural Arica Nafiz, "An overview of character recognition focused on off-line handwriting," in Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on 31. 2 ," , 2001, pp. 216-233.
  5. N. Otsu, "A threshold selection method from gray-level histograms," in IEEE Trans. Systems, Man, and Cybernetics, 1979, pp. 62-66.
  6. P. K. Sahoo, and A. K. C. Wong Kapur J. , "A new method for gray-level picture. Thresholding using the Entropy of the Histogram," in Computer Vision Graphics and Image Processing vol. 29, 1985, pp. 273-285.
  7. Y. and C. G. Leedham Solihin, "Integral Ratio: A New Class of Global Thresholding Techniques for Handwriting images," in IEEE Trans. on PAMI, vol. 21, 1999, pp. 761-768.
  8. Yibing Yang and Hong Yan, "An adaptive logical method for binarization of degraded document images Pattern Recognition," in Pattern Recognition Society, Elsevier Science , vol. 33, no. 5, 2000, pp. 787-807.
  9. and Matti Pietikäinen Sauvola Jaakko, "Adaptive Document Image Binarization," in Pattern Recognition 33. 2, 2000, pp. 225-236.
  10. M Randolph T. Smith, "Enhancement of fax documents using a binary angular representation," in in Proceedings of, Int Symp on Intelligent Multimedia, Video and Speech Processing, Hong Kong,Cjina, 2001.
  11. Wu Sue Adnan Amin, "Automatic Thresholding of Gray-level Using Multi-stage Approach," in in Proceedings of the 7th International Conference on Document Analysis and Recognition (ICDAR 2003),IEEE, 2003.
  12. S. Perantonis Gatos B I. Pratikakis, "An Adaptive Binarization Technique for Low Quality Historical Documents," in Document Analysis Systems VI, vol. 3163, , 2004.
  13. Chen Y. and G. Leedham, "Decompose algorithm for thresholding degraded historical document images," in IEEE Proc. -Vis. Image Signal Process vol. 152, , December 2005.
  14. Chen Y. and G. Leedham, "Document binarization using Kohonen," in IET Image Process, 2007, pp. 67-85.
  15. Ioannis Pratikakis, and Stavros J. Perantonis. Gatos Basilios, "Improved document image binarization by using a combination of multiple binarization techniques and adapted edge information," in Pattern Recognition, vol. ICPR 2008. 19th International Conference on. IEEE, 2008, 2008.
  16. Konstantinos Ntirogiannis, and Ioannis Pratikakis Gatos Basilios, "ICDAR 2009 Document Image Binarization Contest (DIBCO 2009)," in ICDAR, vol. 9, 2009.
  17. Michael S. Brown, and Dong Xu. Huang Yi, "User-assisted ink-bleed reduction," in Image Processing, IEEE Transactions , oct 2010, pp. 2646-2658.
  18. Shijian Lu, and Chew Lim Tan Su Bolan, "Robust document image binarization technique for degraded document images," in Image Processing, IEEE Transactions on 22. 4 , 2013, pp. 1408-1417.
  19. et al. Goral Cindy M. , "Modeling the interaction of light between diffuse surfaces," in ACM SIGGRAPH Computer Graphics, vol. 18, 1984.
  20. and Rendong Zhang Ke Li, "Multiscale wiener filtering method for low-dose CT images," in Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference , vol. 1 IEEE.
  21. J. R. Parker, "Gray level thresholding in badly illuminated images," in IEEE Transactions on Pattern Analysis and Machine Intelligence 13. 8 , 1991, pp. 813-819.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Binarization Techniques Document Segmentation Image Processing Morphological Operators And Thresholding.