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Arabic Offline Character Recognition Model Using Non-dominated Rank Sorting Genetic Algorithm

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 (AISI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1261))

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Abstract

In recent years, there was intensive research on Arabic Optical Character Recognition (OCR), especially the recognition of scanned, offline, machine-printed documents. However, Arabic OCR results are unsatisfactory and are still an evolving research area. Exploring the best feature extraction techniques and selecting an appropriate classification algorithm lead to superior recognition accuracy and low computational overhead. This paper presents a new Arabic OCR approach by integrating both of Extreme Learning Machine (ELM) and Non-dominated Rank Sorting Genetic Algorithm (NRSGA) in a unified framework with the aim of enhancing recognition accuracy. ELM is adopted as a neural network classifier that has a short processing time and avoids many difficulties faced by gradient-based learning methods such as learning epochs and local minima. NSRGA is utilized as a feature selection algorithm that has better convergence and spread of solutions. NSRGA emphasizes ranking among the solutions of the same front, along with elite preservation mechanism, and ensuring diversity through the nearest neighbor method reduces the run-time complexity using the simple principle of space-time trade-off. The Experimental results reveal the efficiency of the proposed model and demonstrated that the features selection approach increases the accuracy of the recognition process.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Institute of Graduate Studies and Research, Alexandria University, Alexandria, Egypt

    Saad M. Darwish

  2. Faculty of Science, Department of Mathematics, Damanhour University, Damanhur, Egypt

    Osama F. Hassan & Khaled O. Elzoghaly

Authors
  1. Saad M. Darwish
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  2. Osama F. Hassan
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  3. Khaled O. Elzoghaly
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Corresponding author

Correspondence to Saad M. Darwish .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Artificial Intelligence, Information Technology Department, and Chair of the Scientific Research Group in Egypt, Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  2. Department of Electronics and Computer Science, Koszalin University of Technology, Koszalin, Poland

    Adam Slowik

  3. Faculty of Electrical Engineering and Computer Science, VÅ B-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  4. Rector of the Electronic Research Institute, Cairo, Egypt

    Hisham El-Deeb

  5. Faculty of computers and information, Ain Shams University, Cairo, Egypt

    Fahmy M. Tolba

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Darwish, S.M., Hassan, O.F., Elzoghaly, K.O. (2021). Arabic Offline Character Recognition Model Using Non-dominated Rank Sorting Genetic Algorithm. In: Hassanien, A.E., Slowik, A., Snášel, V., El-Deeb, H., Tolba, F.M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020. AISI 2020. Advances in Intelligent Systems and Computing, vol 1261. Springer, Cham. https://doi.org/10.1007/978-3-030-58669-0_20

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