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Reseach Article

A Contrast Measure based Approach to Binaries Handwritten Documents through MRF

by Bharti Bansinge, R.K. Pateriya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 15
Year of Publication: 2015
Authors: Bharti Bansinge, R.K. Pateriya
10.5120/ijca2015905752

Bharti Bansinge, R.K. Pateriya . A Contrast Measure based Approach to Binaries Handwritten Documents through MRF. International Journal of Computer Applications. 123, 15 ( August 2015), 34-39. DOI=10.5120/ijca2015905752

@article{ 10.5120/ijca2015905752,
author = { Bharti Bansinge, R.K. Pateriya },
title = { A Contrast Measure based Approach to Binaries Handwritten Documents through MRF },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 15 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number15/22038-2015905752/ },
doi = { 10.5120/ijca2015905752 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:13:06.579715+05:30
%A Bharti Bansinge
%A R.K. Pateriya
%T A Contrast Measure based Approach to Binaries Handwritten Documents through MRF
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 15
%P 34-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Document binarization plays important role to preserve the historical document. Recently number of researcher present numerous techniques of document binarization that can vary in sensitivity, quality and some more control parameters. The document image binarization focuses on extracting the text and background of the image. In doing this the edge detection approach also played the crucial role. In this paper a framework for digitations of historical physical document has been proposed. This framework  suggest to use Markov random function to evaluate contrast of pixel and try to overcome  the problem of appearance of a single document that can vary greatly depending on factors such as lighting, viewing angle. Following that, proposed framework uses this energy to differentiate foreground and background ink. Final binaries image document have significant enhance in PSNR (db) value. Proposed scheme use DIBCO (2013) for evaluation and validation.

References
  1. Reza Farrahi Moghaddamn, Mohamed Cheriet “AdOtsu: An adaptive and parameter less generalization of Otsu’s method for document image binarization”, in Elsevier transaction of Pattern Recognition, pg no: 2419–2431, 2012.
  2. B. Gatos, K. Ntirogiannis, I. Pratikakis, “Document image binarization contest (DIBCO 2009)”, in International Conference on Document Analysis and Recognition, pg no: 1375–1382, 2009.
  3. Pratikakis, I., Gatos, B., Ntirogiannis, K., “Document image binarization contest (DIBCO 2011)”, in International Conference on Document Analysis and Recognition, pg no: 1506–1510, 2011.
  4. Bolan Su, Shijian Lu and Chew Lim Tan, “A Learning Framework for Degraded Document Image Binarization using Markov Random Field” in 21st International Conference on Pattern Recognition (ICPR 2012)November 11-15, IEEE-2012. Tsukuba, Japan
  5. Bolan Su, Shijian Lu, And Chew Lim Tan “Robust Document Image Binarization Technique For Degraded Document Images” in IEEE Transactions On Image Processing, Vol. 22, No. 4, April 2013
  6. David Hebert, Stephane Nicolas and Thierry Paquet “Discrete CRF based combination framework for document image binarization” in 12th International Conference on Document Analysis and Recognition, IEEE-2013
  7. Karthika M Ajay James “A Proposed Method For Document Image Binarization Based on Bit Plane Slicing” in International Conference on Advances in Engineering &Technology Research (ICAETR - 2014), August 01-02,IEEE-2014
  8. M. Sezgin, B. Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging 13 (1), 146–168, 2004.
  9. R. Farrahi Moghaddam, M. Cheriet, “A multi-scale framework for adaptive binarization of degraded document images”, Pattern Recognition 43 (6), 2186–2198, 2010.
  10. B. Gatos, I. Pratikakis, S.J. Perantonis, “Adaptive degraded document image Binarization”, Pattern Recognition 39 (3) 317–327, 2006.
  11. B. Gatos, K. Ntirogiannis, I. Pratikakis, DIBCO 2009: document image binarization contest, International Journal on Document Analysis and Recognition, 1–10, 2010.
  12. J. Fabrizio, B. Marcotegui, M. Cord, “Text segmentation in natural scenes using toggle-mapping”, ICIP’09, pp. 2373–2376, 2009.
  13. B. Gatos, K. Ntirogiannis, I. Pratikakis, ICDAR 2009 document image binarization contest (DIBCO 2009), in: ICDAR’09, pp. 1375–1382, 2009.
  14. R. Hedjam, R. Farrahi Moghaddam, M. Cheriet, “A spatially adaptive statistical method for the binarization of historical manuscripts and degraded document images”, Pattern Recognition 44 (9) 2184–2196, 2011.
  15. B. Su, S. Lu, C.L. Tan, “A self-training learning document binarization frame work”, ICPR’10, pp. 3187–3190, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Document digitization Markov Random field Contrast measurement Gaussian filter Weiner filter