A Statistical Framework for Online Arabic Character Recognition

Baligh M. Al-Helali; Sabri A. Mahmoud

doi:10.1080/01969722.2016.1206768

A Statistical Framework for Online Arabic Character Recognition

Baligh M. Al-Helali, Sabri A. Mahmoud^*

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

The widely-used PDAs, touch screens, tablet-PCs are alternatives to keyboards with the advantages of being more friendly, easy, and natural. A framework for Arabic online character recognition is developed. The framework integrates the different phases of online Arabic text recognition. The used data poses several challenges such as delayed strokes handling, connectivity problems, variability, and style change of text. We process the delayed strokes at the different phases differently to improve the overall performance. This work includes feature extraction of many features, including several novel statistical features. Experimental results on challenging online Arabic characters show encouraging results.

Original language	English
Pages (from-to)	478-498
Number of pages	21
Journal	Cybernetics and Systems
Volume	47
Issue number	6
DOIs	https://doi.org/10.1080/01969722.2016.1206768
State	Published - 17 Aug 2016

Bibliographical note

Publisher Copyright:
© 2016, Copyright © Taylor & Francis Group, LLC.

Keywords

Arabic online text recognition
feature extraction
online character recognition

ASJC Scopus subject areas

Software
Information Systems
Artificial Intelligence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/01969722.2016.1206768

Cite this

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title = "A Statistical Framework for Online Arabic Character Recognition",

abstract = "The widely-used PDAs, touch screens, tablet-PCs are alternatives to keyboards with the advantages of being more friendly, easy, and natural. A framework for Arabic online character recognition is developed. The framework integrates the different phases of online Arabic text recognition. The used data poses several challenges such as delayed strokes handling, connectivity problems, variability, and style change of text. We process the delayed strokes at the different phases differently to improve the overall performance. This work includes feature extraction of many features, including several novel statistical features. Experimental results on challenging online Arabic characters show encouraging results.",

keywords = "Arabic online text recognition, feature extraction, online character recognition",

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AU - Al-Helali, Baligh M.

AU - Mahmoud, Sabri A.

PY - 2016/8/17

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N2 - The widely-used PDAs, touch screens, tablet-PCs are alternatives to keyboards with the advantages of being more friendly, easy, and natural. A framework for Arabic online character recognition is developed. The framework integrates the different phases of online Arabic text recognition. The used data poses several challenges such as delayed strokes handling, connectivity problems, variability, and style change of text. We process the delayed strokes at the different phases differently to improve the overall performance. This work includes feature extraction of many features, including several novel statistical features. Experimental results on challenging online Arabic characters show encouraging results.

AB - The widely-used PDAs, touch screens, tablet-PCs are alternatives to keyboards with the advantages of being more friendly, easy, and natural. A framework for Arabic online character recognition is developed. The framework integrates the different phases of online Arabic text recognition. The used data poses several challenges such as delayed strokes handling, connectivity problems, variability, and style change of text. We process the delayed strokes at the different phases differently to improve the overall performance. This work includes feature extraction of many features, including several novel statistical features. Experimental results on challenging online Arabic characters show encouraging results.

KW - Arabic online text recognition

KW - feature extraction

KW - online character recognition

UR - https://www.scopus.com/pages/publications/84982833798

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JF - Cybernetics and Systems

IS - 6

ER -

A Statistical Framework for Online Arabic Character Recognition

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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Cite this