Future of Information and Communication Conference (FICC) 2023
2-3 March 2023
Publication Links
IJACSA
Special Issues
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.
Off-Line Arabic (Indian) Numbers Recognition Using Expert System
Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070453
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 4, 2016.
Abstract: This paper proposes an effective approach to automatic recognition of printed Arabic numerals which are extracted from digital images. First, the input image is normalized and pre-processed to an acceptable form. From the preprocessed image, components of the words are segmented into individual objects representing different numbers. Second, the numerical recognition is performed using an expert system based on a set of if-else rules, where each set of rules represents the categorization of each number. Finally, rigorous experiments are carried out on 226 random Arabic numerals selected from 40 images of Iraqi car plate numbers. The proposed method attained an accuracy of 97%.
Keywords: Arabic numeral character recognition; Image Processing; Pattern Recognition; Feature Extraction; Object Segmentation; Expert System
Fahad Layth Malallah, Mostafah Ghanem Saeed, Maysoon M. Aziz, Olasimbo Ayodeji Arigbabu and Sharifah Mumtazah Syed Ahmad, “Off-Line Arabic (Indian) Numbers Recognition Using Expert System” International Journal of Advanced Computer Science and Applications(IJACSA), 7(4), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070453
@article{Malallah2016,
title = {Off-Line Arabic (Indian) Numbers Recognition Using Expert System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070453},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070453},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {4},
author = {Fahad Layth Malallah and Mostafah Ghanem Saeed and Maysoon M. Aziz and Olasimbo Ayodeji Arigbabu and Sharifah Mumtazah Syed Ahmad}
}
