Handwritten Arabic (Indian) Numerals Recognition Using Fourier Descriptor and Structure Base Classifier

Authors

  • Shatha M Noor Department of Computer Science, College of Science, University of Al-Nahrain, Baghdad-Iraq.
  • Ihab A Mohammed Department of Computer Science, College of Science, University of Al-Nahrain, Baghdad-Iraq.
  • Loay E George Department of Computer Science, College of Science, University of Baghdad, Baghdad-Iraq.

Keywords:

Digit Recognition, Binarization, Thinning, Segmentation, Edge Connection, Chain Codes, Fourier Descriptor, Structured Classifier

Abstract

In this paper a simple and accurate method is proposed to recognize Arabic (Indian) numerals using Fourier descriptors as the main classifier feature set, and to improve the recognition accuracy a simple structure based classifier is add as a supplementary classifier. The recognition system was tested on 450 samples collected from 5 students and the test results indicate that the recognition ratio is%89.6when only 5 Fourier descriptors are used as discriminating features set, and the ratio is raised to%98 when 4 Fourier descriptors are used in addition to the simple structure based classifier.



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Published

2011-06-01

Issue

Vol. 14 No. 2 (2011): June

Section

Articles

How to Cite

[1]
“Handwritten Arabic (Indian) Numerals Recognition Using Fourier Descriptor and Structure Base Classifier”, ANJS, vol. 14, no. 2, pp. 215–224, Jun. 2011, Accessed: Apr. 27, 2024. [Online]. Available: https://anjs.edu.iq/index.php/anjs/article/view/908