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An Efficient Hybrid Model for Arabic Text Recognition

Hicham Lamtougui1,*, Hicham El Moubtahij2, Hassan Fouadi1, Khalid Satori1

1 LIIAN Laboratory, Faculty of Sciences Dhar-Mahraz, Fez, 30000, Morocco
2 Modeling, Systems and Technologies of Information Team, University of Ibn Zohr, Agadir

* Corresponding Author: Hicham Lamtougui. Email: email

Computers, Materials & Continua 2023, 74(2), 2871-2888. https://doi.org/10.32604/cmc.2023.032550

Abstract

In recent years, Deep Learning models have become indispensable in several fields such as computer vision, automatic object recognition, and automatic natural language processing. The implementation of a robust and efficient handwritten text recognition system remains a challenge for the research community in this field, especially for the Arabic language, which, compared to other languages, has a dearth of published works. In this work, we presented an efficient and new system for offline Arabic handwritten text recognition. Our new approach is based on the combination of a Convolutional Neural Network (CNN) and a Bidirectional Long-Term Memory (BLSTM) followed by a Connectionist Temporal Classification layer (CTC). Moreover, during the training phase of the model, we introduce an algorithm of data augmentation to increase the quality of data. Our proposed approach can recognize Arabic handwritten texts without the need to segment the characters, thus overcoming several problems related to this point. To train and test (evaluate) our approach, we used two Arabic handwritten text recognition databases, which are IFN/ENIT and KHATT. The Experimental results show that our new approach, compared to other methods in the literature, gives better results.

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APA Style
Lamtougui, H., Moubtahij, H.E., Fouadi, H., Satori, K. (2023). An efficient hybrid model for arabic text recognition. Computers, Materials & Continua, 74(2), 2871-2888. https://doi.org/10.32604/cmc.2023.032550
Vancouver Style
Lamtougui H, Moubtahij HE, Fouadi H, Satori K. An efficient hybrid model for arabic text recognition. Comput Mater Contin. 2023;74(2):2871-2888 https://doi.org/10.32604/cmc.2023.032550
IEEE Style
H. Lamtougui, H.E. Moubtahij, H. Fouadi, and K. Satori "An Efficient Hybrid Model for Arabic Text Recognition," Comput. Mater. Contin., vol. 74, no. 2, pp. 2871-2888. 2023. https://doi.org/10.32604/cmc.2023.032550



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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