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An Analysis of Image Binarization Techniques for Natural Scene Images

Published on April 2012 by Dharam Veer Sharma, Sukhdev Singh
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International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
Foundation of Computer Science USA
IRAFIT - Number 5
April 2012
Authors: Dharam Veer Sharma, Sukhdev Singh
9fa7e25d-90c9-4f14-b483-a10696846b20

Dharam Veer Sharma, Sukhdev Singh . An Analysis of Image Binarization Techniques for Natural Scene Images. International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012). IRAFIT, 5 (April 2012), 29-32.

@article{
author = { Dharam Veer Sharma, Sukhdev Singh },
title = { An Analysis of Image Binarization Techniques for Natural Scene Images },
journal = { International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012) },
issue_date = { April 2012 },
volume = { IRAFIT },
number = { 5 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 29-32 },
numpages = 4,
url = { /proceedings/irafit/number5/5883-1039/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%A Dharam Veer Sharma
%A Sukhdev Singh
%T An Analysis of Image Binarization Techniques for Natural Scene Images
%J International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT 2012)
%@ 0975-8887
%V IRAFIT
%N 5
%P 29-32
%D 2012
%I International Journal of Computer Applications
Abstract

Text extraction from natural scene images is an emerging field in computer graphics. Extracted text contains important information that can be used for various purpose like vehicle number plate detection to identify the vehicle, to provide information of surrounding to visually impaired persons, preservation of information of historical documents etc. Binarization is a key process in text extraction process. It is challenging take in case of natural scene images due to uneven lighting conditions, complex background and unpredicted text size, color and layout. Three well known binarization techniques namely Otsu's, Niblack's and Sauvola's binarization techniques are test on natural scene images. We found that, Sauvola's algorithm can achieve better performance than Niblack's. In most of cases Sauvola and Niblack gave good results as compare to Otsu's method. Otsu binarization technique is good for uniform background. Window based Niblack's and Sauvola's methods are useful to find local threshold to binrize natural scene images.

References
  1. Nobuo Ezaki, Marius Bulacu and Lambert Schomaker, "Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons", in the proceedings of 17th International Conference on Pattern Recognition, Cambridge ,UK, vol. 2, 683-686, 2004.
  2. D. E. Ventzas, N. Ntogas, "A Binarization Algorithm for Historical Manuscripts", in the proceedings of 12th WSEAS International Conference on Communications, Greece, pp.41-51, 2008.
  3. M. Sezgin, B. Sankur, "Survey over Image Thresholding Techniques and Quantitative Performance Evaluation", Journal of Electronic Imaging,146-165, 2004.
  4. Wayne Niblack. An Introduction to Digital Image Processing. Prentice Hall, New Jersey, 1986.
  5. J.Sauvola,T,Seppanen, S.Haapakoski and M.Pietikainen, "Adaptive Document Binarization", in proceedings of 4th International Conference on Document Analysis and Recognition, Ulm, Germany, August 1997,147-152.
  6. J. Sauvola, M. Pietikainen, "Adaptive document image binarization", Journal of Pattern Recognition,225-236, 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Binarization otsu Sauvola Images Thresholding Niblack Local Thresholding text Extraction