Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Mouhcine Rabi, Mustapha Amrouch, Zouhir Mahani
10.5120/ijca2017912982

Mouhcine Rabi, Mustapha Amrouch and Zouhir Mahani. A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script. International Journal of Computer Applications 160(2):31-37, February 2017. BibTeX

@article{10.5120/ijca2017912982,
	author = {Mouhcine Rabi and Mustapha Amrouch and Zouhir Mahani},
	title = {A Survey of Contextual Handwritten Recognition Systems based HMMs for Cursive Arabic and Latin Script},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {160},
	number = {2},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {31-37},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume160/number2/27048-2017912982},
	doi = {10.5120/ijca2017912982},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Offline handwriting recognition has become lately a very popular research area and the number of its possible application is very large. Most recognition system are based on modeling characters to recognize, then the concatenation of these models to recognize a word, while modeling character allows deformations related to its context. This paper provides a survey of handwritten recognition systems based on context-dependent character modeling to account possible deformations related to its context. It examines the literature on the most significant work in contextual handwritten text recognition for two different alphabets, Latin and Arabic. Finally discussing the comparative results to achieve a comprehensive summary of the various approaches and systems taking account the character’s context which could help open up some interesting new prospects.

References

  1. Réjean Plamondon, Sargur Srihari “On-line and off-line handwriting recognition: a comprehensive survey”.  in IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1):63-84 · January 2000
  2. K. Gaurav and Bhatia P. K., “Analytical Review of Preprocessing Techniques for Offline Handwritten Character Recognition”, 2nd International Conference on Emerging Trends in Engineering & Management, ICETEM, 2013.
  3. Namrata Dave “Segmentation Methods for Hand Written Character Recognition” International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 4 (2015), pp. 155-164
  4. B. El Qacimy A. Hammouch ; M. A. Kerroum “A review of feature extraction techniques for handwritten Arabic text recognition”. Electrical and Information Technologies (ICEIT), 2015 International Conference
  5. Mohamed Abaynarh and Lahbib Zenkouar, “Offline Handwritten Characters Recognition Using Moments Features and Neural Networks”. Computer Technology and Application 6 (2015)
  6. Priya Sharma, Randhir Singh “Survey and Classification of Character Recognition System” International Journal of Engineering Trends and Technology- Volume4Issue3- 2013
  7. Bhatia Neetu, “Optical Character Recognition Techniques”,International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 5, May 2014.
  8. A.Lawgali : “A Survey on Arabic Character Recognition” International Journal of Signal Processing, Image Processing and Pattern Recognition. Vol. 8, No. 2 (2015), pp. 401-426.
  9. Youssouf Chherawala, Partha Pratim Roy, Mohamed Cheriet “Context-dependent BLSTM models. Applications to offline handwriting recognition” 2014 IEEE International Conference on Image Processing (ICIP)
  10. Gernot A. Fink and Thomas Plotz, “On the use of context-dependent modeling units for HMM-based offline handwriting recognition,” in Proceedings of the 9th International Conference on Document Analysis and Recognition, 2007, vol. 2 of ICDAR ’07, pp. 729–733.
  11. U.-V. Marti and H. Bunke. The IAM-database: An English sentence database for offline handwriting recognition. Int.Journal on Document Analysis and Recognition, 5(1):39– 46, 2002.
  12. Ramy El-Hajj, Chafic Mokbel, and Laurence Likforman-Sulem, “Recognition of Arabic handwritten words using contextual character models,” in DRR, Berrin A. Yanikoglu and Kathrin Berkner, Eds. 2009, vol. 6815 of SPIE Proceedings, p. 681503, SPIE.
  13. M. Pechwitz, S. S. Maddouri, V. Märgner, N. Ellouze, and H. Amiri, “IFN/ENIT - Database of Handwritten Arabic Words,” in 7th Colloque International Francophone sur l’Ecrit et le Document , CIFED 2002, 2002, pp. 129–136.
  14. EL-Hajj R, Mokbel.C Likforman-Sulem L “ Arabic handwriting recognition using baselin dependent features and hidden Markov modeling” Proceedings of the Eighth International Conference on Document Analysis and Recognition ICDAR05, p 893-897, 2005.
  15. Anne-Laure Bianne-Bernard, Far`es Menasri, Ramy Al- Hajj Mohamad, Chafic Mokbel, Christopher Kermorvant, and Laurence Likforman-Sulem, “Dynamic and contextual information in HMM modeling for handwritten word recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 10, pp. 2066–2080, 2011.
  16. Olivier Morillot, Emmanuèle Grosicki , Laurence Likforman-Sulem, « Reconnaissance de courriers manuscrits par HMM contextuels et modèle de langage » DOI:10.3166/DN.16.2.69-90 © 2013 Lavoisier Document numérique – no 2/2013, 69-90
  17. Mahdi Hamdani, Patrick Doetsch and Hermann Ney “Improvement of Context Dependent Modeling for Arabic Handwriting Recognition “ 2014 14th International Conference on frontiers in Handwrting Recognition.
  18. M. Hamdani, P. Doetsch, M. Kozielski, A. El-Desoky Mousa, and H. Ney, “The RWTH large vocabulary Arabic handwriting recognition system,” in International Workshop on Document Analysis Systems, Tours `a Loire Valley, France, Apr. 2014.
  19. Irfan Ahùad, Gernot A.Fink and Sabri A.Mahmoud “Improvement in Sub-character HMM Model Based Arabic Text Recognition” 2014 14th International Conference on frontiers in Handwrting Recognition.
  20. A. Tong, M. Przybocki, V. Maergner, and H. El Abed, "NIST 2013 Open Handwriting Recognition and Translation evaluation", Proceedings of the NIST 2013 Open Handwriting and Recognition Workshop, 2013, in press.
  21. E. Augustin, M. Carre, E. Grosicki, J.-M. Brodin, E. Geoffrois, and F. Preteux, “Rimes Evaluation Campaign for Handwritten Mail Processing,” Proc. Int’l Workshop Frontiers in Handwriting Recognition, pp. 231-235, 2006.
  22. http://rimes.it sudparis.eu/, 2010.

Keywords

Offline handwriting Recognition, Latin, Arabic, Context, Cursive