I There are many methods for enhancement of degraded document images. In the process of improving degraded document images segmentation is one of the difficult task due to background and foreground variation such as uneven illumination, document smear such as smudging of text, seeping of ink to the other side of paper, degradation of paper ink due to aging etc. A number of methodologies have been proposed by several researchers on image segmentation using binarization technique. In document analysis, binarization is easily affected by noise, surrounding illumination, gray-level distribution, local shading effects, weak contrast, and the presence of dense non-text components such as photographs. So binarization can become a challenging job under varying illumination and noise. This survey aims to evaluate the principles of image binarization techniques. The main objective of this paper is to evaluate the different image binarization techniques to find the gaps in existing techniques.

Degraded document image binarization, Global thresholding, Local thresholding, Dynamic thresholding, Adaptive binarization, Hybrid binarization

Otsu, N.:”A threshold selection method from gray-level histogram”.IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)
[2] Niblack, W.: “An introduction to digital image
processing”, pp. 115–116. Prentice Hall, Eaglewood Cliffs (1986)
[3] Moghaddam, R.F., Cheriet, M.: “A multi-scale
framework for adaptive binarization of degraded document images”. Pattern Recogn, 43(6), 2186–2198 (2010)
[4] Bernsen, J.:”Dynamic thresholding of gray level
images”. In: Proceedings of International Conference on Pattern Recognition (ICPR), pp. 1251–1255 (1986)
[5] Ntirogiannis, K., Gatos, B., Pratikakis, I.: “Performance evaluation methodology for historical document image binarization”. IEEE Trans. Image Process.22 (2), 595–609 (2013)
[6] Ntirogiannis, K., Gatos, B., Pratikakis,” A combined
approach for the binarization of Hand written document images”. Pattern Recogn.Lett.35,3–15(2014).(ISSN 0167-8655, http://dx.doi.org/10.1016/j.patrec.2012.09.026)
[7] Valizadeh, M., Kabir, E.: “Binarization of degraded
document image based on feature space partitioning and classification”. Int. J. Doc.Anal.Recogn. (IJDAR) 15(1), 57–69 (2012)
[8] Bataineh, B., Abdullah, S.N.H.S., Omar, K.: “An
adaptive local binarization method for document images based on a novel thresholding method and dynamic windows”. Pattern Recogn.Lett.32 (14), 1805–1813 (2011)
[9] B. Su, S. Lu, and C. L. Tan, “Binarization of historical handwritten document images using local maximum and minimum filter”, International Workshop on Document Analysis Systems, pp. 303–314, June 2010.
[10] Jagroop Kaur1, Dr.Rajiv Mahajan,” A Review of
Degraded Document Image Binarization Techniques”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 5, May 2014, ISSN (Print) : 2319-5940 ISSN (Online) : 2278-1021
[11] N. Chaki et al., “A Comprehensive Survey on Image
Binarization Techniques”, Exploring Image Binarization Techniques, Studies in Computational Intelligence 560, © Springer India 2014