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Efficient Analysis of Vertical Projection Histogram to Segment Arabic Handwritten Characters

Mamouni El Mamoun1,*, Zennaki Mahmoud1, Sadouni Kaddour1

Département Informatique Université des Sciences et de la Technologie d’Oran Mohamed Boudiaf USTO-MB, BP 1505 El M’naoeur, 31000, Oran, Algérie.

* Corresponding Author: Mamouni El Mamoun. Email: email.

Computers, Materials & Continua 2019, 60(1), 55-66. https://doi.org/10.32604/cmc.2019.06444

Abstract

The paper discusses the segmentation of words into characters, which is an essential task in the development process of character recognition systems, as poorly segmented characters will automatically be unrecognized. The segmentation of offline handwritten Arabic text poses a greater challenge because of its cursive nature and different writing styles. In this article, we propose a new approach to segment handwritten Arabic characters using an efficient analysis of the vertical projection histogram. Our approach was tested using a set of handwritten Arabic words from the IFN/ENIT database, and promising results were obtained.

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Cite This Article

M. El Mamoun, Z. Mahmoud and S. Kaddour, "Efficient analysis of vertical projection histogram to segment arabic handwritten characters," Computers, Materials & Continua, vol. 60, no.1, pp. 55–66, 2019.

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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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