Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm
International Journal of Data Science and Analysis
Volume 2, Issue 2, December 2016, Pages: 37-41
Received: Sep. 19, 2016; Accepted: Dec. 14, 2016; Published: Jan. 10, 2017
Views 3377      Downloads 116
Authors
Mustafa Ali Abuzaraida, Computer Science Department, Faculty of Information Technology, Misurata University, Misurata, Libya
Akram M. Zeki, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia
Ahmed M. Zeki, Department of Information Systems, College of Information Technology University of Bahrain, Sakhir, Kingdom of Bahrain
Article Tools
Follow on us
Abstract
Online text recognition systems have been continually given due importance these days globally because of the rapidly developing touch screen gadgets. However, it has been difficult to utilize keyboards and external mouse-like inputs in significantly tinier devices which consequently paved the way to current researched based scientists to look for some newer techniques which could design such type of online systems which could further deal with different kinds of texts for example, digits, symbols and alphabets. In the present paper, an online system for recognizing manually written Arabic numerals is being given. This paper will show digit acquisition, preprocessing, feature extraction and recognition phases in detail. The set of the data was gathered from 100 writers using a touch screen PC with 100 samples of every digit. The average accuracy rate of the outcome of the test of this proposed system was 98%, which is a significant accuracy rate.
Keywords
Arabic Numerals, Handwriting Recognition, Handwritten Numerals, Matching Alignment Algorithm
To cite this article
Mustafa Ali Abuzaraida, Akram M. Zeki, Ahmed M. Zeki, Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm, International Journal of Data Science and Analysis. Vol. 2, No. 2, 2016, pp. 37-41. doi: 10.11648/j.ijdsa.20160202.14
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
M. A. Abuzaraida, A. M. Zeki and A. M. Zeki, "Recognition Techniques for Online Arabic Handwriting Recognition Systems," In Proceeding of the International Conference on Advanced Computer Science Applications and Technologies (ACSAT2012), Kuala Lumpur, Malaysia, 2012.
[2]
Mustafa Ali Abuzaraida, Akram M Zeki and Ahmed M Zeki, "Online Recognition System for Handwritten Hindi Digits Based on Matching Alignment Algorithm," In Proceeding of the Third International Conference on Advanced Computer Science Applications and Technologies (ACSAT2014), Amman, Jordan, 2014.
[3]
Mustafa Ali Abuzaraida, Akram M. Zeki and Ahmed M. Zeki, "Problems of writing on digital surfaces in online handwriting recognition systems," In Proceeding of the Information and Communication Technology for the Muslim World (ICT4M), 2013 5th International Conference on, 2013, pp. 1-5.
[4]
M. A. Abuzaraida, A. M. Zeki and A. M. Zeki, "Segmentation Techniques for Online Arabic Handwriting Recognition: A survey," In Proceeding of the 3rd International Conference on Information and Communication Technology for the Moslem World: ICT Connecting Cultures, ICT4M 2010, Jakarta, Indonesia, 2010, pp. D37-D40.
[5]
R. Kaplan and E. Kaplan, The Nothing that Is: A Natural History of Zero: Oxford University Press, 1999.
[6]
Solomon Gandz, "The Origin of the Ghubār Numerals, or the Arabian Abacus and the Articuli." vol. 16, T. U. o. C. Press, Ed., ed: The University of Chicago Press, pp. 393-424, 1931.
[7]
Mustafa Ali Abuzaraida, Akram M Zeki and Ahmed M Zeki, "Online Database of Quranic Handwritten Words," Journal of Theoretical & Applied Information Technology, vol. 62, 2014.
[8]
Mustafa Ali Abuzaraida, Akram M Zeki, Ahmed M Zeki and Nor Farahidah Za'bah, "Online Recognition System for Handwritten Arabic Chemical Symbols," In Proceeding of the Computer and Communication Engineering (ICCCE), 2014 International Conference on, 2014, pp. 138-141.
[9]
M. A. Abuzaraida, A. M. Zeki and A. M. Zeki, "Difficulties and Challenges of Recognizing Arabic Text," in Computer Applications: Theories and Applications, ed Kuala Lumpur: IIUM Press Malaysia, 2011.
[10]
N. Tagougui, M. Kherallah and A. M. Alimi, "Online Arabic handwriting recognition: a survey," International Journal on Document Analysis and Recognition, pp. 1-18, 2012.
[11]
Mai Al-Ammar, Reham Al-Majed and Hatim Aboalsamh, "Online Handwriting Recognition for the Arabic Letter Set," Recent Researches in Communications and IT, 2011.
[12]
Loader Clive, Local Regression and Likelihood vol. 47: springer New York, 1999.
[13]
Douglas David and Peucker Thomas, "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature," Cartographica: The International Journal for Geographic Information and Geovisualization, vol. 10, pp. 112-122, 1973.
[14]
Mustafa Ali Abuzaraida, Salem Meftah Jebriel, "The detection of the suitable reduction value of Douglas-Peucker algorithm in online handwritten recognition systems". IEEE International Conference on Service Operations And Logistics, And Informatics (SOLI), Hammamet, Tunisia, 2015. pp 82-87.
[15]
M. A. Abuzaraida, Akram M Zeki and Ahmed M Zeki, "Feature Extraction Techniques of Online Handwriting Arabic Text Recognition," In Proceeding of the 5th International Conference on Information and Communication Technology for the Muslim World (ICT4M), 2013, pp. 1-7.
[16]
Freeman Herbert, "Computer Processing of Line-Drawing Images," ACM Comput. Surv., vol. 6, pp. 57-97, 1974.
[17]
R Durbin, S Wddy, A Korgh and G Mitchison, Biological sequence analysis: probabilistic models of proteins and nucleic acids: Cambridge University Press, 1998.
[18]
Neil C. Jones and Pavel A. Pevzner, An Introduction to Bioinformatics Algorithms, illustrated ed. Cambridge, Massachusetts London, England: Massachusetts Institute of Technology Press, 2004.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186