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Reseach Article

Contrast Enhanced Niblack Binarization of Document Images

Published on June 2015 by Sheshera Mysore, Prashant Sharma, Vivek Rai, Priya Charles
National Conference on Emerging Trends in Advanced Communication Technologies
Foundation of Computer Science USA
NCETACT2015 - Number 2
June 2015
Authors: Sheshera Mysore, Prashant Sharma, Vivek Rai, Priya Charles
847d1d71-63c1-4715-a195-6773282dbf9f

Sheshera Mysore, Prashant Sharma, Vivek Rai, Priya Charles . Contrast Enhanced Niblack Binarization of Document Images. National Conference on Emerging Trends in Advanced Communication Technologies. NCETACT2015, 2 (June 2015), 6-10.

@article{
author = { Sheshera Mysore, Prashant Sharma, Vivek Rai, Priya Charles },
title = { Contrast Enhanced Niblack Binarization of Document Images },
journal = { National Conference on Emerging Trends in Advanced Communication Technologies },
issue_date = { June 2015 },
volume = { NCETACT2015 },
number = { 2 },
month = { June },
year = { 2015 },
issn = 0975-8887,
pages = { 6-10 },
numpages = 5,
url = { /proceedings/ncetact2015/number2/20985-2019/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Advanced Communication Technologies
%A Sheshera Mysore
%A Prashant Sharma
%A Vivek Rai
%A Priya Charles
%T Contrast Enhanced Niblack Binarization of Document Images
%J National Conference on Emerging Trends in Advanced Communication Technologies
%@ 0975-8887
%V NCETACT2015
%N 2
%P 6-10
%D 2015
%I International Journal of Computer Applications
Abstract

In this paper we propose a method of document image binarization that performs well on grayscale images with complex backgrounds, maintains good text extraction abilities and retains the graphic features that might be present in the image. The proposed method employs a coarse thresholding step that uses a contrast feature for classification of pixels into foreground and background followed by Niblack thresholding for finer classification of the pixels. The proposed method was found to perform better or at-par with four other popular thresholding methods that it was compared against.

References
  1. M. Sezgin, "Survey over image thresholding techniques and quantitative performance evaluation," J. Electron. Imaging, vol. 13, no. January, pp. 146–165, 2004.
  2. C. -M. Tsai and H. -J. Lee, "Binarization of color document images via luminance and saturation color features. ," IEEE Trans. Image Process. , vol. 11, no. 4, pp. 434–51, Jan. 2002.
  3. E. Badekas, N. Nikolaou, and N. Papamarkos, "Text binarization in color documents," Int. J. Imaging Syst. Technol. , vol. 16, no. 6, pp. 262–274, 2006.
  4. N. Nikolaou and N. Papamarkos, "Color reduction for complex document images," Int. J. Imaging Syst. Technol. , vol. 19, no. 1, pp. 14–26, Mar. 2009.
  5. B. Wang, X. Li, F. Liu, and F. Hu, "Color text image binarization based on binary texture analysis," Pattern Recognit. Lett. , 2005.
  6. J. Matas and J. Kittler, "Spatial and feature space clustering: Applications in image analysis," Comput. Anal. Images Patterns, 1995.
  7. P. Sahoo, S. Soltani, and A. Wong, "A survey of thresholding techniques," Comput. vision, Graph. image, pp. 233–260, 1988.
  8. O. Trier and A. Jain, "Goal-directed evaluation of binarization methods," Pattern Anal. Mach. Intell. 1995.
  9. N. Otsu, "A threshold selection method from gray level histograms," IEEE Trans. Systems, Man and Cybernetics, vol. 9, pp. 62–66, 1979
  10. J. Kittler and J. Illingworth, "Minimum error thresholding," Pattern Recognition, vol. 19, no. 1, pp. 41–47, 1986.
  11. J. Kapur, P. Sahoo, and A. Wong, "A new method for gray-level picture thresholding using the entropy of the histogram," Comput. vision, Graph. image, 1985.
  12. W. Niblack, "An introduction to digital image processing. " Strandberg Publishing Company, 1985.
  13. C. Wolf, J. Jolion, and F. Chassaing, "Text localization, enhancement and binarization in multimedia documents," Pattern Recognition, 2002, pp. 2–5, 2002.
  14. J. Sauvola and M. Pietikäinen, "Adaptive document image binarization," Pattern Recognit. , vol. 33, pp. 225–236, 2000.
  15. B. Su, S. Lu, and C. L. Tan, "Combination of Document Image Binarization Techniques," 2011 Int. Conf. Doc. Anal. Recognit. , pp. 22–26, Sep. 2011.
  16. T. Kuo, Y. Lai, and Y. Lo, "A novel image binarization method using hybrid thresholding," Multimed. Expo (ICME), 2010, pp. 608–612, 2010.
  17. B. Gatos, I. Pratikakis, and S. J. Perantonis, "Improved document image binarization by using a combination of multiple binarization techniques and adapted edge information," 2008 19th Int. Conf. Pattern Recognit. , pp. 1–4, Dec. 2008.
  18. M. J. Taylor and C. R. Dance, "Enhancement of Document Images from Cameras", Proc. of IS&T/SPIE EIDR V, pp. 230-241, 1998.
  19. B. Gatos, K. Ntirogiannis, and I. Pratikakis, "ICDAR 2009 document image binarization contest(DIBCO 2009)," Inter- national Conference on Document Analysis and Recognition, pp. 1375–1382, July 2009.
  20. S. Milyaev and O. Barinova, "Image binarization for end-to-end text understanding in natural images," (ICDAR), 2013 12th, 2013.
  21. T. Kasar, J. Kumar, and A. G. Ramakrishnan, "Font and Background Color Independent Text Binarization," vol. 2, no. 1, pp. 3–9, 2007.
  22. S. Fomel and J. F. Claerbout, "Guest editors' introduction: Reproducible research," Computing in Science and Engineering, vol. 11, no. 1, pp. 5–7, 2009
  23. Bitbucket URL: http://bit. ly/1Hi9H1
Index Terms

Computer Science
Information Sciences

Keywords

Document Image Processing Binarization Niblack Thresholding