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.
| Published in | International Journal of Data Science and Analysis (Volume 2, Issue 2) |
| DOI | 10.11648/j.ijdsa.20160202.14 |
| Page(s) | 37-41 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Arabic Numerals, Handwriting Recognition, Handwritten Numerals, Matching Alignment Algorithm
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APA Style
Mustafa Ali Abuzaraida, Akram M. Zeki, Ahmed M. Zeki. (2017). Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm. International Journal of Data Science and Analysis, 2(2), 37-41. https://doi.org/10.11648/j.ijdsa.20160202.14
ACS Style
Mustafa Ali Abuzaraida; Akram M. Zeki; Ahmed M. Zeki. Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm. Int. J. Data Sci. Anal. 2017, 2(2), 37-41. doi: 10.11648/j.ijdsa.20160202.14
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Download@article{10.11648/j.ijdsa.20160202.14,
author = {Mustafa Ali Abuzaraida and Akram M. Zeki and Ahmed M. Zeki},
title = {Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm},
journal = {International Journal of Data Science and Analysis},
volume = {2},
number = {2},
pages = {37-41},
doi = {10.11648/j.ijdsa.20160202.14},
url = {https://doi.org/10.11648/j.ijdsa.20160202.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20160202.14},
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.},
year = {2017}
}
TY - JOUR T1 - Online Recognition Approach of Arabic Numerals Using Matching Alignment Algorithm AU - Mustafa Ali Abuzaraida AU - Akram M. Zeki AU - Ahmed M. Zeki Y1 - 2017/01/10 PY - 2017 N1 - https://doi.org/10.11648/j.ijdsa.20160202.14 DO - 10.11648/j.ijdsa.20160202.14 T2 - International Journal of Data Science and Analysis JF - International Journal of Data Science and Analysis JO - International Journal of Data Science and Analysis SP - 37 EP - 41 PB - Science Publishing Group SN - 2575-1891 UR - https://doi.org/10.11648/j.ijdsa.20160202.14 AB - 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. VL - 2 IS - 2 ER -
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