Abstract
Handwriting recognition is a complicated process that many applications rely on, such as mail sorting, cheque processing, digitalisation and translation. The recognition of handwritten Arabic is still an ongoing challenge mainly due to the similarity among its letters and the variety of writing styles. In this paper, a novel approach is proposed that uses support vector machines (SVMs) with normalized poly kernel. The well-known Arabic handwritten database, IFN/ENIT-database, which contains 936 city names with more than 32,492 instances, is used to test the proposed system. The results of this novel approach are compared with the results of two different studies. The comparison shows that a higher accuracy rate is obtained using the proposed system.
Keywords
- SVM
- Offline word recognition
- Normalized poly kernel
- Feature extraction
This is a preview of subscription content, access via your institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Farghaly, A., Shaalan, K.: Arabic Natural Language Processing: Challenges and Solutions, vol. 8, pp. 14:1–14:22 (2009)
Aburas, A.A., Rehiel, S.A.: Comprehensive Review for Arabic Handwriting and Printed Characters Recognition. In: Intell. Adv. Syst. ICIAS, pp. 730–735 (2007)
Aburas, A.A., Gumah, M.E.: Arabic Handwriting Recognition: Challenges and Solutions. In: International Symposium on Information Technology, pp. 1–6 (2008)
El Abed, H., Margner, V.: Comparison of Different Preprocessing and Feature Extraction Methods for Offline Recognition of Handwritten Arabic Words. In: 9th International Conference on Document Analysis and Recognition, pp. 974–978 (2007)
Genchi, H., Mori, K., Watanabe, S., Katsuragi, S.: Recognition of Handwritten Numerical Characters for Automatic Letter Sorting. Pro. IEEE 56, 1292–1301 (1968)
Masterson, J.L., Hirsch, R.S.: Machine Recognition of Constrained Handwritten Arabic Numbers. IRE Transactions on Human Factors in Electronics HFE-3, 62–65 (1962)
Almuallim, H., Yamaguchi, S.: A method of recognition of Arabic cursive handwriting. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-9, 715–722 (1987)
Margner, V., Abed, H.E.: Arabic Handwriting Recognition Competition. In: International Conference on Document Analysis and Recognition, ICDAR, pp. 1444–1448 (2011)
Cheriet, M., Kharma, M., Liu, C., Suen, C.: Character Recognition Systems: A Guide for Students and Practitioners. John Wiley & Sons, Inc., Hoboken (2007)
El Affar, A., Ferdous, K., El Fadili, H., Qjidaa, H.: Krawtchouk Moment Feature Extraction for Neural Arabic Handwritten Words Recognition. In: International Conference Multimedia Computing and Systems, pp. 443–448 (2009)
El-Feghi, I., Elmahjoub, F., Alswady, B., Baiou, A.: Offline Handwritten Arabic Words Recognition Using Zernike Moments and Hidden Markov Models. In: International Conference on Computer Applications and Industrial Electronics, ICCAIE, pp. 165–168 (2010)
Hamdi, R., Bouchareb, R., Bedda, M.: Handwritten Arabic Character Recognition Based on SVM Classifier. In: 3rd International Conference on Information and Communication Technologies: From Theory to Applications, ICTTA, pp. 1–4 (2008)
Khalifa, M., BingRu, Y.: A Novel Word Based Arabic Handwritten Recognition System Using SVM Classifier. In: Shen, G., Huang, X. (eds.) ECWAC 2011, Part I. CCIS, vol. 143, pp. 163–171. Springer, Heidelberg (2011)
Almaádeed, S., Higgens, C., Elliman, D.: Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach. In: Proceedings of 16th International Conference on Pattern Recognition, vol. 3, pp. 481–484 (2002)
Ben Cheikh, I., Kacem, A.: Neural Network for the Recognition of Handwritten Tunisian City Names. In: 9th International Conference on Document Analysis and Recognition, pp. 1108–1112 (2007)
Benouareth, A., Ennaji, A., Sellami, M.: HMMs with Explicit State Duration Applied to Handwritten Arabic Word Recognition. In: 18th International Conference on Pattern Recognition, pp. 897–900 (2006)
Touj, S.M., Ben Amara, N.E., Amiri, H.: A Hybrid Approach for Off-Line Arabic Handwriting Recognition Based on a Planar Hidden Markov Modeling. In: 9th International Conference on Document Analysis and Recognition, ICDAR, pp. 964–968 (2007)
AlKhateeb, J.H., Khelifi, F., Jianmin, J., Ipson, S.S.: A New Approach for Off-Line Handwritten Arabic Word Recognition Using KNN Classifier. In: IEEE International Conference Signal and Image Processing Applications, pp. 191–194 (2009)
Nasien, D., Haronand, H., Yuhaniz, S.S.: Support Vector Machine (SVM) for English Handwritten Character Recognition. In: Second International Conference on Computer Engineering and Applications, pp. 249–252 (2010)
Nemmour, H., Chibani, Y.: Handwritten Arabic Word Recognition Based on Ridgelet Transform and Support Vector Machines. In: International Conference on High Performance Computing and Simulation, HPCS, pp. 357–361 (2011)
Kahraman, F., Capar, A., Ayvaci, A., Demirel, H., Gokmen, M.: Comparison of SVM and ANN Performance for Handwritten Character Classification. In: Proceedings of the 12th IEEE Signal Processing and Communications Applications Conference, pp. 615–618 (2004)
Vapnik, V.N.: An Overview of Statistical Learning Theory. IEEE Trans. Neural Networks 10, 988–999 (1999)
Hsu, C.W., Lin, C.J.: A Comparison of Methods for Multiclass Support Vector Machines. IEEE Trans. Neural Networks 13, 415–425 (2002)
Milgram, J., Cheriet, M., Sabourin, R.: One against One or One against All: Which One Is Better for Handwriting Recognition with SVMs? Presented at Tenth International Workshop on Frontiers in Handwriting Recognition (2006)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA Data Mining Software: An Update. SIGKDD Explor. Newsl. 11, 10–18 (2009)
Pechwitz, M., Snoussi Maddouri, S., Margner, V., Ellouze, N., Amiri, H.: IFN/ENIT-Database of Handwritten Arabic Words. In: 7th Colloque International Francophone sur lEcrit et le Document, CIFED, Hammamet, Tunis, pp. 21–23 (2002)
El-Melegy, M.T., Abdelbaset, A.A.: Global Features for Offline Recognition of Handwritten Arabic Literal Amounts. In: 5th International Conference on Information and Communications Technology, ITI, pp. 125–129 (2007)
Lorigo, L.M., Govindaraju, V.: Offline Arabic Handwriting Recognition: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 28, 712–724 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alalshekmubarak, A., Hussain, A., Wang, QF. (2012). Off-Line Handwritten Arabic Word Recognition Using SVMs with Normalized Poly Kernel. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-34481-7_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34480-0
Online ISBN: 978-3-642-34481-7
eBook Packages: Computer ScienceComputer Science (R0)
