Advertisement

Visual Recognition of Arabic Handwriting: Challenges and New Directions

  • Mohamed Cheriet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4768)

Abstract

Automatic recognition of Arabic handwritten text presents a problem worth solving; it has increasingly more interest, especially in recent years. In this paper, we address the most frequently encountered problems when dealing with Arabic handwriting recognition, and we briefly present some lessons learned from several serious attempts. We show why morphological analysis of Arabic handwriting could improve the accuracy of Arabic handwriting recognition. In general, Arabic Natural Language Processing could provide some error handling techniques that could be used effectively to improve the overall accuracy during post-processing. We give a summary of techniques concerning Arabic handwriting recognition research. We conclude with a case study about the recognition of Tunisian city names, and place emphasis on visual-based strategies for Arabic Handwriting Recognition (AHR).

Keywords

Hide Markov Model Natural Language Processing Visual Recognition Word Class Arabic Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cheriet, M.: Strategies for Visual Arabic Handwriting Recognition. Issues and Case Study. In: IEEE Int. Conference on Signal Processing and Applications, Sharjah (UAE) (2007) (invited paper)Google Scholar
  2. 2.
    Cheriet, M., Beldjehem, M.: Visual Processing of Arabic Handwriting: Challenges and New Directions. In: Summit on Arabic and Chinese Handwriting (SACH 2006), Washington-DC, pp. 129–136 (2006) (invited paper) Google Scholar
  3. 3.
    Belaid, A., Choisy, C.: Human Reading Based Strategies Off-line Arabic Word Recognition. In: Summit on Arabic and Chinese Handwriting (SACH 2006), Washington-DC, USA, pp. 137–144 (2006) (invited paper)Google Scholar
  4. 4.
    Magner, V., El Abed, H.: Databases and Competitions – Strategies to improve Arabic Recognition Systems. In: Summit on Arabic and Chinese Handwriting (SACH 2006), Washington-DC, pp. 145–153 (2006) (invited paper)Google Scholar
  5. 5.
    Al-Ohali, Y., Cheriet, M., Suen, C.Y.: Databases for Recognition of Handwritten Arabic cheques. Journal of Pattern Recognition 36, 111–121 (2003)zbMATHCrossRefGoogle Scholar
  6. 6.
    Al-Sughaiyer, I.A., Al-Kharashi, I.A.: Arabic Morphological Analysis Techniques. Journal of the American Society for Inf. Sc. and Tech. 55(3), 189–213 (2004)CrossRefGoogle Scholar
  7. 7.
    Miled, H.: Stratégies de résolution en reconnaissance de l’écriture semi-cursive: Application aux mots manuscrits arabes. PhD thesis, PSI-La3i UnivRouen, LIVIA ETS, Montreal (1998)Google Scholar
  8. 8.
    Miled, M., Olivier, C., Cheriet, M., Lecourtier, Y.: Coupling observation/letter for a Markovian modeling applied to the recognition of Arabic handwriting. In: Proc. ICDAR, Ulm, Germany, pp. 580–583 (1997)Google Scholar
  9. 9.
    Miled, H., Cheriet, M., Olivier, C.: Multi-level Arabic Handwritten Words Recognition. In: Proc. SSPR/SPR, pp. 944–951 (1998)Google Scholar
  10. 10.
    JSimon, J.C., Baret, O.: Handwriting recognition as an application of regularities and singularities in line pictures. In: Proc. of IWFHR, Montreal, pp. 23–36 (1990)Google Scholar
  11. 11.
    Hani, A., et al.: Deterministic and nondeterministic flow-chart interpretations. JASIS 50(6), 524–529 (1999)CrossRefGoogle Scholar
  12. 12.
    Adnan, A., et al.: Handwritten Arabic Character recognition by the IRAC system. In: Proc. Int. Conf. on Pattern Recognition, Miami, pp. 729–731 (1980)Google Scholar
  13. 13.
    Adnan, A., et al.: Recognition of Handwritten Arabic Scripts and Sentences. In: Proc. ICPR, Montreal, (2), pp. 1055–1057 (1984)Google Scholar
  14. 14.
    Al-Badr, B., Mahmoud, S.: Survey and bibliography of Arabic Optical text recognition. Signal Processing 41, 49–77 (1995)zbMATHCrossRefGoogle Scholar
  15. 15.
    Al-Emami, S., Usher, M.: On-line recognition of handwritten Arabic characters. IEEE Trans. PAMI 12(7), 704–710 (1990)Google Scholar
  16. 16.
    Almuallim, H., Yamaguchi, S.: A method for recognition of Arabic cursive handwriting. IEEE Trans. PAMI 9(5), 715–722 (1987)Google Scholar
  17. 17.
    Souici-Meslati, L.L., Sellami, M.: A Hybrid Neuro-Symbolic Approach for Arabic Handwritten Word Recognition. JACII 10(1), 17–25 (2006)Google Scholar
  18. 18.
    Souici-Meslati, L., Farah, N., Sari, T., Sellami, M.: Rule Based Neural Networks Construction for Handwritten Arabic City-Names Recognition. In: Bussler, C.J., Fensel, D. (eds.) AIMSA 2004. LNCS (LNAI), vol. 3192, pp. 331–340. Springer, Heidelberg (2004)Google Scholar
  19. 19.
    Al-sheikh, T.S., El-Taweel, S.G.: Real-time Arabic handwritten character recognition. Journal of Pattern Recognition 23(12), 1323–1332 (1990)CrossRefGoogle Scholar
  20. 20.
    Abuhaiba, S.I., Ahmed, P.: Restoration of temporal information in off-line Arabic handwriting. Journal of Pattern Recognition 26(7), 1009–1017 (1993)CrossRefGoogle Scholar
  21. 21.
    Abuhaiba, I.S.I., Mahmoud, S.A., Green, R.J.: Recognition of Handwritten Cursive Arabic Characters. IEEE Trans. PAMI 16(6), 664–672 (1994)Google Scholar
  22. 22.
    Mahmoud, S.A., Abuhaiba, S.I., Green, R.J.: Skeletonization of Arabic characters using clustering based skeletonization algorithm (CBSA). Journal of Pattern Recognition 24(5), 453–464 (1991)CrossRefGoogle Scholar
  23. 23.
    Pechwitz, M., Snoussi-Maddouri, S., Margner, V., Ellouze, N., Amiri, H.: IFN/ENIT database of handwritten Arabic words. In: Proc. Colloque Francophone International sur l’Écrit et le Document, Hammamet, pp. 129–136 (2002)Google Scholar
  24. 24.
    Hull, J.J.: A Database for handwritten text recognition research. IEEE Trans. PAMI 16, 550–554 (1994)Google Scholar
  25. 25.
    Zadeh, L.A.: The Roles of Fuzzy Logic and Soft Computing in the Conception, Design, and Development of Intelligent Systems. In: Nwana, H.S., Azarmi, N. (eds.) Software Agents and Soft Computing: Towards Enhancing Machine Intelligence. LNCS, vol. 1198, pp. 183–190. Springer, Heidelberg (1997)Google Scholar
  26. 26.
    Zadeh, L.A.: Soft Computing, Fuzzy Logic and Recognition Technology. In: Proc. IEEE Int. Conf. Fuzzy Systems, Anchorage, AK, pp. 1678–1679 (1998)Google Scholar
  27. 27.
    Zadeh, L.A.: Some Reflections on Soft Computing, Granular Computing and their Roles in the Conception, Design and Utilization of Information/Intelligent Systems. Soft Computing 2, 23–25 (1998)Google Scholar
  28. 28.
    Beldjehem, M., Cheriet, M.: Validation and Verification of Hybrid Min-Max Fuzzy Systems. In: Proc. North American Fuzzy Information Processing (NAFIPS 2006), Montreal, Canada (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Mohamed Cheriet
    • 1
  1. 1.Laboratory for Imagery, Vision and Artificial IntelligenceÉcole de Technologie Supérieure (University of Quebec)MontrealCanada

Personalised recommendations