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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Handwritten Arabic Text Recognition using Principal Component Analysis and Support Vector Machines

Author 1: Faisal Al-Saqqar
Author 2: Atallah. M AL-Shatnawi
Author 3: Mofleh Al-Diabat
Author 4: Mesbah Aloun

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0101227

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

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Abstract: In this paper, an offline holistic handwritten Arabic text recognition system based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) classifiers is proposed. The proposed system consists of three primary stages: preliminary processing, feature extraction using PCA, and classification using the polynomial, linear, and Gaussian SVM classifiers. In this proposed system, text skeleton is first extracted and the images of the text are normalized into uniform size for extraction of the global features of the Arabic words using PCA. Recognition performance of this proposed system was evaluated on version 2 of the IFN/ENIT database of handwritten Arabic text using the polynomial, linear, and Gaussian SVM classifiers. The classification results of the proposed system were compared with the results produced by a benchmark. TRS that is depending on the Discrete Cosine Transform (DCT) method using numerous normalization sizes of Arabic text images. The experimental testing results support the effectiveness of the proposed system in holistic recognition of the handwritten Arabic text.

Keywords: Handwritten Arabic text; holistic recognition; principal component analysis; support vector machines

Faisal Al-Saqqar, Atallah. M AL-Shatnawi, Mofleh Al-Diabat and Mesbah Aloun, “Handwritten Arabic Text Recognition using Principal Component Analysis and Support Vector Machines” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101227

@article{Al-Saqqar2019,
title = {Handwritten Arabic Text Recognition using Principal Component Analysis and Support Vector Machines},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101227},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101227},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Faisal Al-Saqqar and Atallah. M AL-Shatnawi and Mofleh Al-Diabat and Mesbah Aloun}
}


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