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Research Article | Open Access |

Off-Line Arabic (Indian) Numbers Recognition Using Expert System

Author 1: Fahad Layth Malallah Author 2: Mostafah Ghanem Saeed Author 3: Maysoon M. Aziz Author 4: Olasimbo Ayodeji Arigbabu Author 5: Sharifah Mumtazah Syed Ahmad
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 4 · Published 2016 · Cited by 5

DOI: https://doi.org/10.14569/IJACSA.2016.070453

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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

How to Cite this Article

Malallah, F. L., Saeed, M. G., Aziz, M. M., Arigbabu, O. A., & Ahmad, S. M. S. (2016). Off-Line Arabic (Indian) Numbers Recognition Using Expert System. International Journal of Advanced Computer Science and Applications, 7(4). https://doi.org/10.14569/IJACSA.2016.070453

Malallah, Fahad Layth, et al.. "Off-Line Arabic (Indian) Numbers Recognition Using Expert System." International Journal of Advanced Computer Science and Applications, vol. 7, no. 4, 2016, https://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},
  volume    = {7},
  number    = {4},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Fahad Layth Malallah and Mostafah Ghanem Saeed and Maysoon M. Aziz and Olasimbo Ayodeji Arigbabu and Sharifah Mumtazah Syed Ahmad},
  doi       = {10.14569/IJACSA.2016.070453},
  url       = {https://doi.org/10.14569/IJACSA.2016.070453}
}

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