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A Review of Document Image Binarization Techniques

Pritpal Singh1 , Balwinder Singh2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 746-749, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.746749

Online published on Jun 30, 2019

Copyright © Pritpal Singh, Balwinder Singh . 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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IEEE Style Citation: Pritpal Singh, Balwinder Singh, “A Review of Document Image Binarization Techniques,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.746-749, 2019.

MLA Style Citation: Pritpal Singh, Balwinder Singh "A Review of Document Image Binarization Techniques." International Journal of Computer Sciences and Engineering 7.6 (2019): 746-749.

APA Style Citation: Pritpal Singh, Balwinder Singh, (2019). A Review of Document Image Binarization Techniques. International Journal of Computer Sciences and Engineering, 7(6), 746-749.

BibTex Style Citation:
@article{Singh_2019,
author = {Pritpal Singh, Balwinder Singh},
title = {A Review of Document Image Binarization Techniques},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {746-749},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4624},
doi = {https://doi.org/10.26438/ijcse/v7i6.746749}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.746749}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4624
TI - A Review of Document Image Binarization Techniques
T2 - International Journal of Computer Sciences and Engineering
AU - Pritpal Singh, Balwinder Singh
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 746-749
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

Binarization is very important pre-processing technique for document images which is used to segment the image into foreground and background pixels. Binarization of degraded documents is very challenging due to uneven background, noise, ink dots, degradation of paper ink due to aging etc. Although many binarization techniques are available, but these standard algorithms are sensitive to noise and do not produce good results on different kinds of degradations. The selection of binarization method for a particular degradation is a very tedious job. In this paper, a survey of recent ongoing research efforts in field of image binarization has been carried out. The purpose of this study is to find the research gap in the field of document image binarization.

Key-Words / Index Term

Binarization, Degraded documents, Thresholding, OCR, Document images

References

[1] F. Jia, C. Shi, K. He, C. Wang, B. Xiao, “Degraded document image binarization using structural symmetry of strokes”, Pattern Recognition, Vol. 74, pp. 225-240, 2018.
[2] F. Jia, C. Shi, K. He, C. Wang, B. Xiao, “Document image binarization using structural symmetry of strokes”, In the proceedings of 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), Shenzhen, China, pp. 411-416, 2016.
[3] S. Bolan, S. Lu, C.L. Tan, “Robust document image Binraization technique for degraded document images” IEEE Transactions on Image Processing, Vol. 22, Issue 4, pp. 1408-1417, 2013.
[4] S. Mysore, M.K. Gupta, S. Behle, “Complex and degraded color document image binarization”, In the proceedings of 2016 3rd International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 157-162, 2016.
[5] J. Bernsen, “Dynamic Thresholding of Gray Level Image”, In the proceedings of International Conference on Pattern Recognition ICPR`86, Berlin, pp. 1251-1255, 1986.
[6] J. Saulva, M. Pietikäinen, “Adaptive document image binarization”, Pattern Recognition, Vol. 33, Issue 2, pp. 225-236, 2000.
[7] O. Boudraa, W.K. Hidouci, D. Michelucci “A robust multi stage technique for image binarization of degraded historical documents” In the proceedings of 5th International Conference on Electrical Engineering (ICEE-B), Boumerdes, pp. 1-6, 2017.
[8] K. Ntirogiannis, B. Gatos, I. Pratikakis “A combined approach for the binarization of handwritten document images” Pattern Recognition Letters, Vol. 35, pp. 3-15, 2014.
[9] J.S. Valverde, R.R. Grigat. “Optimum binarization of technical document images”, In the proceedings of International Conference on Image Processing. Vancouver, Canada, pp. 985-988, 2000.
[10] N. Chaki, S.H. Shaikh, K. Saeed, “A Comprehensive Survey on Image Binarization Techniques” In Exploring Image Binarization Techniques. Vol. 560. Springer, India, pp. 5-15, 2014.
[11] B. Su, S. Lu, C.L. Tan. “Combination of document image binarization techniques”, In the proceedings of International Conference on Document Analysis and Recognition (ICDAR), Beijing, China, pp. 22-26, 2011.
[12] R. Firdousi, S. Parveen. “Local Thresholding Techniques in Image Binarization” International Journal of Engineering and Computer Science, Vol. 3, No. 3, pp. 4062-4065, 2014.
[13] Ø.D. Trier, T. Taxt, “Evaluation of binarization methods for document images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, Issue 3, pp. 312-315, 1995.
[14] G. Leedham, C. Yan, K. Takru, J.H.N. Tan, L. Mian, “Comparison of some thresholding algorithms for text/background segmentation in difficult document images”, In the proceedings of Seventh International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, UK, pp. 859-864, 2003.
[15] N. Otsu, “A threshold selection method from gray-level histograms”, IEEE transactions on systems, man, and cybernetics, Vol. 9, Issue 1, pp. 62-66, 1979.
[16] B. Gatos, I. Pratikakis, S.J. Perantonis, “Adaptive degraded document image binarization”, Pattern Recognition, Vol. 9, Issue 3, pp. 317-327, 2006.
[17] M.K. Jindal, R.K. Sharma, G.S. Lehal, “A study of different kinds of degradation in printed Gurmukhi script”. In the proceedings of International Conference on Computing: Theory and Applications, (ICCTA`07), Kolkata, India, pp. 538-544, 2007.
[18] Ø.D. Trier, A.K. Jain, “Goal-directed evaluation of binarization methods”, IEEE Transactions on Pattern Analysis & Machine Intelligence, Vol. 17, Issue 12, pp. 1191-1201, 1995.
[19] P.K. Sahoo, S. Soltani, A.K.C. Wong, Y.C. Chen, “A survey of thresholding techniques” ,Computer vision, graphics, and image processing, Vol. 41, Issue 2, pp. 233-260, 1988.