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Data Document Image Binarization for Preserving Historical: A Review

Bharti Bansinge1 , R.K.Pateriya 2

Section:Review Paper, Product Type: Journal Paper
Volume-3 , Issue-6 , Page no. 108-112, Jun-2015

Online published on Jun 29, 2015

Copyright © Bharti Bansinge , R.K.Pateriya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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How to Cite this Paper

IEEE Style Citation: Bharti Bansinge , R.K.Pateriya, “Data Document Image Binarization for Preserving Historical: A Review,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.108-112, 2015.

MLA Style Citation: Bharti Bansinge , R.K.Pateriya "Data Document Image Binarization for Preserving Historical: A Review." International Journal of Computer Sciences and Engineering 3.6 (2015): 108-112.

APA Style Citation: Bharti Bansinge , R.K.Pateriya, (2015). Data Document Image Binarization for Preserving Historical: A Review. International Journal of Computer Sciences and Engineering, 3(6), 108-112.

BibTex Style Citation:
@article{Bansinge_2015,
author = {Bharti Bansinge , R.K.Pateriya},
title = {Data Document Image Binarization for Preserving Historical: A Review},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2015},
volume = {3},
Issue = {6},
month = {6},
year = {2015},
issn = {2347-2693},
pages = {108-112},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=560},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=560
TI - Data Document Image Binarization for Preserving Historical: A Review
T2 - International Journal of Computer Sciences and Engineering
AU - Bharti Bansinge , R.K.Pateriya
PY - 2015
DA - 2015/06/29
PB - IJCSE, Indore, INDIA
SP - 108-112
IS - 6
VL - 3
SN - 2347-2693
ER -

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Abstract

The basic requirement of physical document analysis system is to digitalize the physical document. Recently number of researcher presented numerous techniques that can vary in sensitivity, quality and some more control parameters. Document binarization plays an important role in preserving the historical documents. The document image binarization focuses on extracting the text and background of the image. In doing this the edge detection approach also play the crucial role. This paper presents general review on the various approaches of document binarization. Various edge detection approaches are also been discussed. In addition various available data sets for image binarization developed in Document Image Binarization Contest (DIBCO) 2009 and Handwritten Document Image Binarization Competition (H-DIBCO) 2011 has also discussed.

Key-Words / Index Term

Document Digitization, Edge Detection, Gaussian Filter

References

[1] Reza Farrahi Moghaddamn, Mohamed Cheriet “AdOtsu: An adaptive and parameterless generalization of Otsu’s method for document image binarization”, Elsevier transaction of Pattern Recognition,2012, pg no- 2419–2431.
[2] B. Gatos, K. Ntirogiannis, I. Pratikakis, ICDAR 2009 document image binarization contest (DIBCO 2009), ICDAR’09,2009, pp. 1375–1382.
[3] Pratikakis, I., Gatos, B., Ntirogiannis, K.: ICDAR 2011 document image binarization contest (DIBCO 2011), International Conference on Document Analysis and Recognition,2011, pp. 1506–1510.
[4] M. Sezgin, B. Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging 13 (1),2004, pp.146–168.
[5] R. Farrahi Moghaddam, M. Cheriet, “A multi-scale framework for adaptive binarization of degraded document images”, Pattern Recognition 43 (6),2010, pp. 2186–2198.
[6] B. Gatos, I. Pratikakis, S.J. Perantonis, “Adaptive degraded document image Binarization”, Pattern Recognition 39 (3),2006, pp. 317–327.
[7] B. Gatos, K. Ntirogiannis, I. Pratikakis, DIBCO 2009: document image binarization contest, International Journal on Document Analysis and Recognition, 2010,pp. 1-10.
[8] J. Fabrizio, B. Marcotegui, M. Cord, “Text segmentation in natural scenes using toggle-mapping”, ICIP’09, 2009, pp. 2373–2376.
[9] B. Gatos, K. Ntirogiannis, I. Pratikakis, ICDAR 2009 document image binarization contest (DIBCO 2009), in: ICDAR’09,2009, pp. 1375–1382.
[10] 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),2011, pp.2184–2196.
[11] B. Su, S. Lu, C.L. Tan, “A self-training learning document binarization frame work”, ICPR’10,2010, pp. 3187–3190.