Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

A Hybrid Image Binarization Technique for Enhancement of Degraded Document Images

Author : Dr. S.Vijayarani 1 M.Geetha 2

Date of Publication :6th October 2017

Abstract: Image processing is a process of analysis and manipulation of digital images, which improves the quality of an image. Image binarization is a pre-processing step which improves the quality of the image. Image binarization is used to improve the image quality and it segment the pixel values into two categories; i.e. black pixel as foreground and white pixel as background. In this research work, binarization techniques are applied to improve the quality of the degraded document images. Different types of image binarization methods used in this work are Otsu, Nick, Niblack and Sauvola. In addition to this, a new hybrid binarization method is proposed which is a combination of local and global method. Performance factors used are PSNR (Peak Signal to Noise Ratio) and NRM (Negative Rate Metric). From the results, it is observed that the proposed hybrid binarization has produced good results than existing methods.

Reference :

    1. Soharab Hossain Shaikh, Asis Kumar Maiti, NabenduChaki,”A new image binarization method using iterative partitioning”,SpringerVerlag 2012.
    2. N.Chaki,”Exploring Image Binarization Techniques”, Studies in Computational Intelligence 560, Springer India 2014.
    3. B.Gatos, P.Pratikakis, S.J.Perantonis,”Adaptive degraded image binarization”, www.elsevier.com/local/patcog.
    4. Jyotsna, Shivani Chauhan, Ekta Sharma, Amit Doegar,”Binarization Techniques for Degraded Document Images-A Review”, International Conference on Reliability,Infocom Technologies and Optimization (ICRITO)(Trends and Future Direction) Sep 2016.
    5. J. Sauvola, M. PietikaKinen,”Adaptive document image binarization”, Pattern Recognition 33 (2000) 225-236, www.elseiver.com.
    6. Mayur Sonar,”Image Segmentation and Binarization Technique for Manuscript”,International Journal of Advanced Research in Computer and Communication EngineeringVol. 5, Issue 1, January 2016
    7. G.Chautani, T.Patnaik, V.Diwedi,”An Improved Approach for automatic Denoising and Binarization of Degraded Document Image based on Region Localization”,IEEE, pp 2272- 2278, 2015.
    8. S.Mandail, A.Agarwae, B.Chanda,”Binarization of Degraded Handwritten Documents on Morphological Contrast Intensification”, Third International Conference on Image Information Processing, pp.73-78, 2015.
    9. B.Biwas, U.Bhattacharya,B.Chanudhuri,”Global to Local Approach to Binarization of Degraded Document Images”, 22nd International Conference on Pattern Recognition, pp.3008- 3013, 2014.
    10. T.K Gill,” Document Image Binarization Techniques –A Review”, International Journal of Advanced Research in Computer and Communication Engineering, Vol.3 Issue 5, May 2014.
    11. B.Su, S.Lu, C.L.Tan, Member,”Robust Documents Image Binarization Techniques for Degraded Documents Images”, IEEE Transactions On Image Processing, Vol 22, No.4, pp. 1408-1417, April 2013.
    12. Sezgin, M., Sankur, B.: Survey over image thresholding techniques and quantitative performance evaluation. J. Electr. Imaging, 146– 165 (2004). [13]Rodriguez, R.Arobust algorithm for binarization of objects. Latin Am. Appl Res40(2010)
    13. Rodriguez, R.: Binarization of medical images based on the recursive application of mean shift filtering: another algorithm. Adv. Chem. 1, 1–12 (2008)
    14. Valizadeh, M., Armanfard, N., Komeili, M., Kabir E.: A novel hybrid algorithm for binarization of badly illuminated document images. In: 14th International CSI Computer Conference (CSICC), pp. 121–126 (2009)
    15. Kawano, H, Oohama, K., Maeda, H., Okada, Y, Ikoma, N, ”Degraded document image binarization combining local statistics”. In: ICROS-SICE International Joint Conference, August 18–21 (2009)

Recent Article