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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.

Characters Segmentation from Arabic Handwritten Document Images: Hybrid Approach

Author 1: Omar Ali Boraik
Author 2: M. Ravikumar
Author 3: Mufeed Ahmed Naji Saif

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130447

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 4, 2022.

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Abstract: Character segmentation in Unconstrained Arabic handwriting is a complex and challenging task due to the overlapping and touching of words or letters. Such issues have not been widely investigated in the literature. Addressing these issues in the segmentation stage reduces errors in the segmentation process, which plays a significant role in enhancing the accuracy of the Arabic optical character recognition. Therefore, this paper proposes a hybrid approach to improve the accuracy for interconnection, overlapping or touching character segmentation. The proposed method includes several stages: removing extra shapes such as signatures from the document. Using morphological operations, connected components and bounding box detection, detect and extract individual words directly from the document. Finally, the touching characters segmentation is achieved based on background thinning and computational analysis of the word's region. The proposed method has been tested on KHATT, IFN/ENIT database and our own collected dataset. The experimental results showed that the proposed method obtained high performance and improved the accuracy compared to other methods.

Keywords: Arabic handwritten character recognition; connected components; word segmentation; character segmentation; morphological operators; overlapping and touching characters

Omar Ali Boraik, M. Ravikumar and Mufeed Ahmed Naji Saif, “Characters Segmentation from Arabic Handwritten Document Images: Hybrid Approach” International Journal of Advanced Computer Science and Applications(IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130447

@article{Boraik2022,
title = {Characters Segmentation from Arabic Handwritten Document Images: Hybrid Approach},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130447},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130447},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {4},
author = {Omar Ali Boraik and M. Ravikumar and Mufeed Ahmed Naji Saif}
}


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