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Reseach Article

Segmentation of Overlapped Handwritten Arabic Sub-Words

Published on April 2015 by Hashem Ghaleb, P. Nagabhushan, Umapada Pal
National conference on Digital Image and Signal Processing
Foundation of Computer Science USA
DISP2015 - Number 2
April 2015
Authors: Hashem Ghaleb, P. Nagabhushan, Umapada Pal
c9e004b1-788e-4867-a304-7d5d3e02471f

Hashem Ghaleb, P. Nagabhushan, Umapada Pal . Segmentation of Overlapped Handwritten Arabic Sub-Words. National conference on Digital Image and Signal Processing. DISP2015, 2 (April 2015), 24-29.

@article{
author = { Hashem Ghaleb, P. Nagabhushan, Umapada Pal },
title = { Segmentation of Overlapped Handwritten Arabic Sub-Words },
journal = { National conference on Digital Image and Signal Processing },
issue_date = { April 2015 },
volume = { DISP2015 },
number = { 2 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 24-29 },
numpages = 6,
url = { /proceedings/disp2015/number2/20486-3018/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National conference on Digital Image and Signal Processing
%A Hashem Ghaleb
%A P. Nagabhushan
%A Umapada Pal
%T Segmentation of Overlapped Handwritten Arabic Sub-Words
%J National conference on Digital Image and Signal Processing
%@ 0975-8887
%V DISP2015
%N 2
%P 24-29
%D 2015
%I International Journal of Computer Applications
Abstract

Arabic script is cursive in both handwritten and printed form. Segmentation of Arabic script- especially handwritten- is a very challenging task. Many difficulties arise due to the inherent characteristics of Arabic writing such as the overlapping of Arabic sub-words wherein the sub-words share the same vertical space, and vertical ligatures wherein characters are stacked upon each other in a word. In this paper, an algorithm to resolve the overlapping of handwritten Arabic sub-words is introduced. The proposed algorithm is based on pushing strategy; sub-words are pushed in order to obtain a clear vertical cut separating the sub-words. The proposed algorithm was tested using handwritten text selected from four different datasets and the results are quite promising.

References
  1. A. Cheung, M. Bennamoun, and N. W. Bergmann. An Arabic optical character recognition system using recognition-based segmentation, Pattern Recognition, Vol. 34, No. 2, pp. 215-233, 2001.
  2. N. Farah, L. Souici, and M. Sellami. . Decision fusion and contextual information for Arabic word recognition for computing and informatics, Computing and Informatics, Vol. 24, No. 5, pp. 463-479, 2012.
  3. M. Elzobi, A. Al-Hamadi , Z. Al Aghbari, and L. Dings. . IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach, International Journal of Document Analysis and Recognition , Vol. 16, No. 3, pp. 295-308, 2013.
  4. L. M. Lorigo and V. Govindaraju. Offline Arabic Handwriting Recognition: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 5, pp. 712-724, 2007.
  5. A. M. AL-Shatnawi, F. H. AL-Zawaideh, S. AL-Salaimeh, and K. Omar. Offline Arabic Text Recognition – An Overview, World of Computer Science and Information Technology Journal, Vol. 1, No. 5, pp. 184-192, 2011.
  6. M. Zand, A. N. Nilchi, and S. A. Monadjemi. Recognition-based Segmentation in Persian Character Recognition, World Academy of Science, Engineering and Technology, Vol. 2, pp. 183-187, 2008.
  7. A. Alaei, P. Nagabhushn, and U. Pal. A New Dataset of Persian Handwritten Documents and Its Segmentation, In proceedimgs of 7th Iranian conference on Machine Vision and Image Processing, pp. 1-5, 2011.
  8. S. A. Mahmoud, I. Ahmad, W. G. Al-Khatib, and M. Alshayeb. KHATT:An open Arabic offline handwritten text database, Pattern Recognition, Vol. 47, No. 3, pp. 1096-112, 2014.
  9. M. Pechwitz, S. S. Maddouri, V. Märgner, N. Ellouze, and H. Amiri. IFN/ENIT- Database of Handwritten Arabic Words, In CIFED : colloque international francophone sur l'e?crit et le document, 2002.
  10. H. A. AlHamad and R. A. Zitar. . Development of an efficient neural-based segmentation technique for Arabic handwriting recognition, Pattern Recognition, Vol. 43, No. 8, pp. 2773–2798, 2010.
  11. H. A. AlHamad. Over-Segmentation of Handwriting Arabic Scripts using an Efficient Heuristic Technique, In proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, pp. 180-185, 2012.
  12. M. Elzobi, A. Al-Hamadi, L. Dinges, and B. Michaelis. . A Structural Features Based Segmentation for Off-line Handwritten Arabic Text, In proceedings of 5th Internationl Symposium on I/V Communication and Mobile Network, pp. 1-4, 2010.
  13. M. T. Parvez and S. A. Mahmoud. Arabic handwriting recognition using structural and syntactic pattern attributes, Pattern Recognition, Vol. 46, No. 1, pp. 141-154, 2013.
  14. A. Alaei, P. Nagabhushan and U. Pal. A Baseline Dependent Approach for Persian Handwritten Character Segmentation, In proceeding of the twentieth International Conference On Pattern Recognition, pp. 1977-1980, 2010.
  15. S. N. Srihari, G. R. Ball and H. Srinivasan. Versatile Search of Scanned Arabic Handwriting, In Arabic and Chinese Handwritten Recognition Summit, SACH 06, pp. 57-69, 2006.
  16. D. Lopresti, G. Nagy, S. Seth, and X. Zhang. Multi-Character field recognition for Arabic and Chinese handwriting, In Arabic and Chinese Handwritten Recognition Summit, SACH 06, pp. 93-100, 2006.
  17. A. Zidouri. ORAN: a basis for an Arabic OCR system, In proceedings of International Symposium on Intelligent Media, Video, and Speech Processing, pp. 703-706, 2004.
Index Terms

Computer Science
Information Sciences

Keywords

Arabic Sub-words Overlapping Arabic Sub-words Resolving Overlapped Arabic Sub-words.