Extraction of Arabic Handwriting Fields by Forms Matching


Filling forms is one of the most useful and powerful ways to collect information from people in business, education and many other domains. Nowadays, almost everything is computerized. That creates a curtail need for extracting these handwritings from the forms in order to get them into the computer systems and databases. In this paper, we propose an original method that will extract handwritings from two types of forms; bank and administrative form. Our system will take as input any of the two forms already filled. And according to some statistical measures our system will identify the form. The second step is to subtract the filled form from a previously inserted empty form. In order to make the acting easier and faster a Fourier-Melin transform was used to re-orient the forms correctly. This method has been evaluated with 50 handwriting forms (from both types Bank and University) and the results were approximatively 90%.

Share and Cite:

Bensefia, A. (2015) Extraction of Arabic Handwriting Fields by Forms Matching. Journal of Signal and Information Processing, 6, 1-8. doi: 10.4236/jsip.2015.61001.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Graves, A., Liwicki, M., Fernandez, S., Bertolami, R., Bunke, H. and Schmidhuber, J. (2009) A Novel Connectionist System for Unconstrained Handwriting Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 855-868.
[2] Lorigo, L.M. and Govindaraju, V. (2006) Offline Arabic Handwriting Recognition: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28, 712-724.
[3] Plamondon, R. and Srihari, S.N. (2000) Online and Off-Line Handwriting Recognition: A Comprehensive Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22, 63-84.
[4] Senior, A.W. and Robinson, A.J. (1998) An Off-Line Cursive Handwriting Recognition System. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20, 309-321.
[5] Koch, G., Heutte, L. and Paquet, T. (2003) Numerical Sequence Extraction in Handwritten Incoming Mail Documents. Seventh International Conference on Document Analysis and Recognition, 1, 369-373.
[6] Chatelain, C., Heutte, L. and Paquet, T. (2004) A Syntax-Directed Method for Numerical Field Extraction Using Classifier Combination. 9th International Workshop on Frontiers in Handwriting Recognition IWFHR-9, 26-29 October 2004, 93-98.
[7] Clawson, R. and Barrett, W. (2012) Extraction of Handwriting in Tabular Document Images. Family History Technology Workshop at Rootstech.
[8] Samoud, F.B., Maddouri, S.S., Abed, H.E. and Ellouze, N. (2008) Comparison of Two Handwritten Arabic Zones Extraction Methods of Complex Documents. Proceedings of International Arab Conference on Information Technology, Hammamet, 1-7.
[9] Otsu. N. (1979) A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man and Cybernetics, 9, 62-66. http://dx.doi.org/10.1109/TSMC.1979.4310076
[10] Adam, S., Rousseau, F., Ogier, J.M., Cariou, C., Mullot, R., Labiche, J. and Gardes, J. (2001) A Multi-Scale and Multi-Orientation Recognition Technique Applied to Document Interpretation Application to French Telephone Network Maps. IEEE International Conference on Acoustics, Speech, and Signal Processing, 3, 1509-1512.
[11] Liu, Q., Zhu, H.Q. and Li, Q. (2011) Object Recognition by Combined Invariants of Orthogonal Fourier-Mellin moments. 8th International Conference on Information, Communications and Signal Processing (ICICS), Singapore, 13-16 December 2011, 1-5.
[12] Sharma, V.D. (2010) Generalized Two-Dimensional Fourier-Mellin Transform and Pattern Recognition. 3rd International Conference on Emerging Trends in Engineering and Technology (ICETET), Goa, 19-21 November 2010, 476-481.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.