We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Document Image Binarization Techniques, Developments and Related Issues: A Review

by Rashmi Saini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 7
Year of Publication: 2015
Authors: Rashmi Saini
10.5120/20352-2541

Rashmi Saini . Document Image Binarization Techniques, Developments and Related Issues: A Review. International Journal of Computer Applications. 116, 7 ( April 2015), 41-44. DOI=10.5120/20352-2541

@article{ 10.5120/20352-2541,
author = { Rashmi Saini },
title = { Document Image Binarization Techniques, Developments and Related Issues: A Review },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 7 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number7/20352-2541/ },
doi = { 10.5120/20352-2541 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:30.480917+05:30
%A Rashmi Saini
%T Document Image Binarization Techniques, Developments and Related Issues: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 7
%P 41-44
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image binarization is still a relevant research area due to its wide range of applications in the field of document analysis and recognition. Accuracy of binarization methods affected by many factors such as shadows non-uniform illumination, low contrast, large signal-dependent noise etc. This paper provides a comprehensive survey of major binarization techniques. We also emphasis on the problems being encountered and the related issues in the research area of document image binarization. In addition, some important issues affecting the performance of image binarization methods are also discussed. This literature review suggests that designing a suitable document image binarization method is a prerequisite for a successful document image analysis and recognition.

References
  1. N. Otsu, "A threshold selection method from gray-level histograms", IEEE Transaction on Systems Man and Cybernetics (SMC), Vol. 9, pp. 62-66, 1979.
  2. J. Kittler, M. Hatef, R. Duin, J. Matas, On combining classifiers, IEEE Trans. Pattern Anal. Mach. Intell. 20 (3) (1998) 226–239.
  3. J. Sauvola, M. Pietikainen, "Adaptive Document Image Binariation", Pattern Recognition, Vol. 33, pp. 225- 236, 2000.
  4. Mehmet Sezgin, B. Sankur, "Survey over image thresholding techniques and quantitative performance evaluation", International Journal of Electronic Imaging(IJEI) Vol. 13 No. 1, pp. 146-165, 2004.
  5. Graham Leedham, Chen Yan, Kalyan Takru, Joie Hadi Nata Tan and Li Mian, "Comparison of Some Thresholding Algorithms for Text/Background Segmentation in Difficult Document Images", IEEE International conference on Document Analysis and Recognition (ICDAR), pp. 859-864, 2003.
  6. Naveed Bin Rais, M. Shehzad Hanif and rmtiaz A. Taj, "Adaptive Thresholding Technique for Document Image Analysis", 8th IEEE International Multitopic Conference, Vol. 3, pp. 61-66, 2004.
  7. Bilal Bataineh, Siti Norul Huda, Sheikh Abdullah, Khairuddin Omar, "An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows", Pattern Recognition Letters Vol. 32, pp. 1805-1813, 2011.
  8. Pierre D. Wellner "Adaptive thresholding for digital desk" Technical Report( EPC) pp. 93-110, 1993.
  9. W. A. Yasnoff, J. K. Mui, and J. W. Bacus, "Error measures for scene segmentation," Pattern Recognition, vol. 9(4), pp. 217-231, 1977
  10. Moghaddam, R. F. , Cheriet, M. : AdOtsu: an adaptive and parameter less generalization of Otsu's method for document image binarization. Pattern Recogn. 45(6), 2419–2431 (2012)
  11. Bernsen, J. : Dynamic thresholding of gray level images. In: Proceedings of International Conference on Pattern Recognition (ICPR), pp. 1251–1255 (1986)
  12. Bradley, D. , Roth, G. : Adaptive thresholding using the integral image. J. Graph. Tools 12(2), 13–21 (2007)
  13. Anjos, A. , Shahbazkia, H. : Bi-level image thresholding—a fast method. Biosignals 2, 70–76(2008)
  14. Gatos, B. , Pratikakis, I. , Perantonis, S. J. : Adaptive degraded document image binarization. Pattern Recogn. 39(3), 317–327 (2006)
  15. Kapur, N. J. , Sahoo, P. K. , Wong, C. K. A. : A new method for gray-level picture thresholding using the entropy of the histogram. J. Comput. Vis. Graph. Image Process. 29(3), 273–285 (1985)
  16. Niblack, W. : An introduction to digital image processing, pp. 115–116. Prentice Hall,Eaglewood Cliffs (1986)
  17. Ntirogiannis, K. , Gatos, B. , Pratikakis, I. : A combined approach for the binarization of handwritten document images. Pattern Recogn. Lett. 35, 3–15 (2014).
  18. Stathis, P. , Kavallieratou, E. , Papamarkos, N. : An evaluation technique for binarization algorithms. J. Univers. Comput. Sci. 14(18), 3011–3030 (2008)
  19. Ntirogiannis, K. , Gatos, B. , Pratikakis, I. : An objective evaluation methodology for document image binarization techniques. In: 8th IAPR Workshop on Document Analysis Systems (2008)
  20. Zhang, C. , Yang, J. , 2010. Binarization of document images with complex background. In: Proc. 6th Internat. Conf. in Wireless Communications Networking and Mobile Computing (WiCOM), pp. 1–4. 2010
  21. P. K. Sahoo, S. Soltani, "A survey of thresholding techniques", Computer Vision Graphics Image Processing(CVGIP). Vol. 41, pp. 233–260. 1988.
  22. Su, B. , Lu, S. , Tan, C. L. : Robust document image binarization technique for degraded document images. IEEE Trans. Image Process. 22(4), 1408–1417 (2013)
  23. Mehmet Sezgin, B. Sankur, "Survey over image thresholding techniques and quantitative performance evaluation", International Journal of Electronic Imaging(IJEI) Vol. 13 No. 1, pp. 146-165, 2004.
  24. Nikhil R. Pal and Sankar K. Pal, "A review on Image segmentation techniques", Pattern Recognition Vol. 26 No. 9 pp. 1277-1294, 1993.
  25. . Wolf, J-M. Jolion, "Extraction and Recognition of Artificial Text in Multimedia Documents", Pattern Analysis and Applications, 6(4):309-326, (2003).
  26. Meng-Ling Feng and Yap-Peng Tan, "Contrast adaptive binarization of low quality document images", IEICE Electron. Express, Vol. 1, No. 16, pp. 501-506, (2004).
  27. Kefali, A. , Sari, T. , Sellami, M. , Evaluation of several binarization techniques for old Arabic documents images. In: The First Internat. Symp. on Modeling and Implementing Complex Systems (MISC'2010), Algeria, pp. 88–99 , 2010
  28. Wellner, P. D. Adaptive thresholding for the digitaldesk. Tech. Rep. EPC-93-110, EuroPARC, 1993
Index Terms

Computer Science
Information Sciences

Keywords

Image binarization Thresholding Segmentation Optical Character Recognition(OCR).