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Gabor Wavelet Recognition Approach for Off-Line Handwritten Arabic Using Explicit Segmentation

  • Moftah Elzobi
  • Ayoub Al-Hamadi
  • Zaher Al Aghbari
  • Laslo Dings
  • Anwar Saeed
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 233)

Summary

This article proposes an un-constrained recognition approach for the handwritten Arabic script. The approach starts by explicitly segment each word image into its constituent letters, then a filter-bank of Gabor wavelet transform is used to extract feature vectors corresponding to different scales and orientation in the segmented image. Classification is carried out by employing a support vectors machine algorithm, where IESK-arDB and IFN/ENIT databases are used for testing and evaluation of the proposed approach respectively. A Leave-one-out estimation strategy is followed to assess performance, where results confirmed the approach efficiency.

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References

  1. 1.
    Abuhaiba, I.S.I., Holt, M.J.J., Datta, S.: Recognition of off-line cursive handwriting. Computer Vision and Image Understanding 71(1), 19–38 (1998)CrossRefGoogle Scholar
  2. 2.
    Al-Badr, B.H.: A segmentation-free approach to text recognition with application to Arabic text. Ph.D. thesis, Seattle, WA, USA (1995)Google Scholar
  3. 3.
    Al-Hajj Mohamad, R., Likforman-Sulem, L., Mokbel, C.: Combining slanted-frame classifiers for improved hmm-based arabic handwriting recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(7), 1165–1177 (2009)CrossRefGoogle Scholar
  4. 4.
    Almuallim, H., Yamaguchi, S.: A method of recognition of arabic cursive handwriting. IEEE Trans. Pattern Anal. Mach. Intell. 9, 715–722 (1987)CrossRefGoogle Scholar
  5. 5.
    Atici, A.A., Yarman-Vural, F.T.: A heuristic algorithm for optical character recognition of arabic script. Signal Processing 62(1), 87–99 (1997)MATHCrossRefGoogle Scholar
  6. 6.
    Bushofa, B.: Segmentation and recognition of arabic characters by structural classification. Image and Vision Computing 15(3), 167–179 (1997)CrossRefGoogle Scholar
  7. 7.
    Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, 27:1–27:27 (2011), software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
  8. 8.
    Chen, J., Cao, H., Prasad, R., Bhardwaj, A., Natarajan, P.: Gabor features for offline arabic handwriting recognition. In: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, DAS 2010, pp. 53–58. ACM, New York (2010)Google Scholar
  9. 9.
    Elzobi, M., Al-Hamadi, A., Al Aghbari, Z., Dings, L.: Iesk-ardb: a database for handwritten arabic and an optimized topological segmentation approach. International Journal on Document Analysis and Recognition (IJDAR), 1–14 (2012)Google Scholar
  10. 10.
    Haboubi, S., Maddouri, S., Ellouze, N., El-Abed, H.: Invariant primitives for handwritten arabic script: A contrastive study of four feature sets. In: 10th International Conference on Document Analysis and Recognition, ICDAR 2009, pp. 691–697 (2009)Google Scholar
  11. 11.
    Hamamoto, Y., Uchimura, S., Watanabe, M., Yasuda, T., Mitani, Y., Tomita, S.: A gabor filter-based method for recognizing handwritten numerals. Pattern Recognition 31(4), 395–400 (1998)CrossRefGoogle Scholar
  12. 12.
    Lorigo, L., Govindaraju, V.: Offline arabic handwriting recognition: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(5), 712–724 (2006)CrossRefGoogle Scholar
  13. 13.
    Madhvanath, S., Govindaraju, V.: The role of holistic paradigms in handwritten word recognition. IEEE Trans. Pattern Anal. Mach. Intell. 23(2), 149–164 (2001)CrossRefGoogle Scholar
  14. 14.
    Pechwitz, M., Maergner, V.: Hmm based approach for handwritten arabic word recognition using the ifn/enit - database. In: Proceedings. Seventh International Conference on Document Analysis and Recognition, pp. 890–894 (2003)Google Scholar
  15. 15.
    Pechwitz, M., Maddouri, S.S., Märgner, V., Ellouze, N., Amiri, H.: Ifn/enit - database of handwritten arabic words. In: Proc. of CIFED 2002, Tunis, pp. 129–136 (2002)Google Scholar
  16. 16.
    Xiu, P., Peng, L., Ding, X.-q., Wang, H.: Offline Handwritten Arabic Character Segmentation with Probabilistic Model. In: Bunke, H., Spitz, A.L. (eds.) DAS 2006. LNCS, vol. 3872, pp. 402–412. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Moftah Elzobi
    • 1
  • Ayoub Al-Hamadi
    • 1
  • Zaher Al Aghbari
    • 2
  • Laslo Dings
    • 1
  • Anwar Saeed
    • 1
  1. 1.Institute for Information Technology and Communications (IIKT)MagdeburgGermany
  2. 2.Computer Science DepartmentUniversity of SharjahSharjahUAE

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