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International Conference on Hybrid Intelligent Systems

HIS 2016: Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) pp 113–123Cite as

Hybrid TDNN-SVM Algorithm for Online Arabic Handwriting Recognition

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 552))

Abstract

This paper deals with a new system of online Arabic handwriting recognition based on the association of beta-elliptic modeling extractor with a hybrid Time Delay Neural Network (TDNN) and Support Vector Machines (SVM) classifier. The beta-elliptic model proceeds by a segmentation of the handwriting trajectory into fragments called Beta strokes by inspecting the extremums points of the curvilinear velocity and extracting their corresponding static and dynamic profile proprieties. These features are used to train the Time Delay Neural Network which is able to represent the sequential aspect of the input data. The fuzzy outputs of this network are then used to train SVM in order to predict the correct label class. To evaluate our method, we have used a total of 25000 Arabic letters from the LMCA database. Experimental results demonstrate the effectiveness of our proposed method and show recognition rate reaching the 99.52%.

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References

  1. Tagougui, N., Kherallah, M., Alimi, A.: Online Arabic handwriting recognition: a survey. Int. J. Doc. Anal. Recogn. (IJDAR) 16(3), 209–226 (2013)

    Article  Google Scholar 

  2. Chaabouni, A., Boubaker, H., Kherallah, M., Alimi, A.M.: Combining of off-line and on-line feature extraction approaches for writer identification. In: International Conference on Document Analysis and Recognition, pp. 1299–1303 (2011)

    Google Scholar 

  3. Maalej, R., Tagougui, N., Kherallah, M.: Online Arabic handwriting recognition with dropout applied in deep recurrent neural networks. In: 12th IAPR Workshop on Document Analysis Systems, pp. 417–421 (2016)

    Google Scholar 

  4. Abdelazeem, S., Hesham, M.: On-line Arabic handwritten personal names recognition based on HMM. In: International Conference on Document Analysis and Recognition System, pp. 1304–1308 (2013)

    Google Scholar 

  5. Nakkach, H., Haboubi, S., Amiri, H.: Online Arabic character recognition using global and local features. In: 3rd International Conference on Automation, Control, Engineering and Computer Science, pp. 120–124 (2016)

    Google Scholar 

  6. Kherallah, M., Bouri, F., Alimi, A.M.: On-line Arabic handwriting recognition system based on visual encoding and genetic algorithm. Eng. Appl. Artif. Intell. 22, 153–170 (2009)

    Article  Google Scholar 

  7. Charfi, M., Kherallah, M., El Baati A., Alimi, Adel M.: A new approach for Arabic handwritten postal addresses recognition. Int. J. Adv. Comput. Sci. Appl. 3(3) (2012)

    Google Scholar 

  8. Daifallah, K., Jamous, H.: Recognition-based segmentation algorithm for on-line Arabic handwriting. In: 10th International Conference on Document Analysis and Recognition, pp. 886–890 (2011)

    Google Scholar 

  9. Tagougui, N., Boubaker, H., Kherallah, M., Alimi, A.M.: A hybrid NN/HMM modeling technique for online Arabic handwriting. Int. J. Comput. Linguist. Res. 4(3), 107–118 (2013)

    Google Scholar 

  10. Hamdani, M., El Abed, H., Kherallah, M., Alimi, A.M.: Combining multiple HMMs using on-line and off-line features for off-line Arabic handwriting recognition. In: 10th International Conference on Document Analysis and Recognition, pp. 201–205 (2010)

    Google Scholar 

  11. Elleuch, M., Zouari, R., Kherallah, M.: Feature extractor based deep method to enhance online Arabic handwritten recognition system. In: Villa, A.E.P., Masulli, P., Pons Rivero, A.J. (eds.) ICANN 2016. LNCS, vol. 9887, pp. 136–144. Springer, Heidelberg (2016). doi:10.1007/978-3-319-44781-0_17

    Chapter  Google Scholar 

  12. Boubaker, H., Kherallah, M., Alimi, A.M.: Handwriting and hand drawing velocity modeling by superposing beta impulses and continuous training component. Int. J. Comput. Sci. Issues 10(5), 57–63 (2013)

    Google Scholar 

  13. Boubaker, H., Kherallah, M., Alimi, A.M.: New strategy for the on line handwriting modeling. In: 9th International Conference on Document Analysis and Recognition, vol. 2, pp. 1233–1247 (2009)

    Google Scholar 

  14. Kherallah, M., Haddad, L., Alimi, A.M.: On-line handwritten digit recognition based on trajectory and velocity modeling. Pattern Recogn. Lett. 29(5), 580–594 (2008)

    Article  Google Scholar 

  15. Plamondon, R., Alimi, A.M.: Modeling velocity profiles of rapid movements: a comparative study. Biol. Cybemetics 69(2), 119–128 (1993)

    Article  Google Scholar 

  16. Dhieb T., Ouarda W., Alimi, A.M.: Online Arabic writer identification based on beta-elliptic model. 15th International Conference on Intelligent Systems Design and Applications, pp. 74–79 (2015)

    Google Scholar 

  17. Waibel, A., Hinton, G.: Phoneme recognition using time delay neural network. IEEE Trans. Acoust. Speech Sig. Process. 37(3), 328–339 (1989)

    Article  Google Scholar 

  18. Ferrat, F., Guerti, M.: Classification of the Arabic emphatic consonants using time delay neural network. Int. J. Comput. Appl. 80(10), 106–112 (2013)

    Google Scholar 

  19. Poisson, E., Lallican, P.: Multi-modular architecture based on convolutional neural networks for online handwritten character recognition. In: Proceedings of the 9th International Conference on Neural Information Processing, vol. 5, pp. 2444–2448 (2002)

    Google Scholar 

  20. Tagougui, N., Boubaker, H., Kherallah, M., Alimi, A.M.: Hybrid MLPNN/HMM recognition system for online Arabic handwritten script. In: World Congress on Computer and Information Technology, pp. 1–6 (2013)

    Google Scholar 

  21. Boubaker, H., Kherallah, M., Alimi, A.M.: Spatio-temporal representation of 3D hand trajectory based on beta-elliptic models. J. Inf. Assur. Secur. 18(15), 1632–1647 (2016)

    Google Scholar 

  22. Elleuch, M., Maalej, R., Kherallah, M.: A new design based-SVM of the CNN classifier architecture with dropout for offline arabic handwritten recognition. Procedia Comput. Sci. 80, 1712–1723 (2016)

    Article  Google Scholar 

  23. Shigeo, A.: Fuzzy support vector machines for multi-label classification. Pattern Recogn. 48(6), 2110–2117 (2015)

    Article  Google Scholar 

  24. Boubaker, H., Elbaati, A., Tagougui, N., Kherallah, M., Alimi, A.M.: Online Arabic databases and applications. In: Märgner, V., El Abed, H. (eds.) Guide to OCR for Arabic Scripts, pp. 541–557. Springer, Heidelberg (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. National School of Engineers of Sfax (ENIS), University of Sfax, Sfax, Tunisia

    Ramzi Zouari & Houcine Boubaker

  2. Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia

    Monji Kherallah

Authors
  1. Ramzi Zouari
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  2. Houcine Boubaker
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  3. Monji Kherallah
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Corresponding author

Correspondence to Ramzi Zouari .

Editor information

Editors and Affiliations

  1. (MIR Labs), Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

  4. Technopolis Rabat-Shore Rocade, International University of Rabat, Sala el Jadida, Morocco

    Ghita Mezzour

  5. Inst Applied Dept of Electronics, Taffala, University of Sousse, Sousse, Tunisia

    Nizar Rokbani

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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© 2017 Springer International Publishing AG

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Zouari, R., Boubaker, H., Kherallah, M. (2017). Hybrid TDNN-SVM Algorithm for Online Arabic Handwriting Recognition. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_12

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  • DOI: https://doi.org/10.1007/978-3-319-52941-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52940-0

  • Online ISBN: 978-3-319-52941-7

  • eBook Packages: EngineeringEngineering (R0)

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