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A Fuzzy Logic based Handwritten Numeral Recognition System

by Mahmood K Jasim, Anwar M Al-saleh, Alaa Aljanaby
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 10
Year of Publication: 2013
Authors: Mahmood K Jasim, Anwar M Al-saleh, Alaa Aljanaby
10.5120/14487-2796

Mahmood K Jasim, Anwar M Al-saleh, Alaa Aljanaby . A Fuzzy Logic based Handwritten Numeral Recognition System. International Journal of Computer Applications. 83, 10 ( December 2013), 36-43. DOI=10.5120/14487-2796

@article{ 10.5120/14487-2796,
author = { Mahmood K Jasim, Anwar M Al-saleh, Alaa Aljanaby },
title = { A Fuzzy Logic based Handwritten Numeral Recognition System },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 10 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 36-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number10/14487-2796/ },
doi = { 10.5120/14487-2796 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:59:02.116482+05:30
%A Mahmood K Jasim
%A Anwar M Al-saleh
%A Alaa Aljanaby
%T A Fuzzy Logic based Handwritten Numeral Recognition System
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 10
%P 36-43
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a delayed treatment to handwritten numerals with fuzzy logic has been provided. The patterns which used in this system consisted 100 patterns of 10 numerals (0 to 9). They were taken from 10 different subjects and converted by the scanner to computer into 30×20 binary patterns. We used off-line system in take the patterns. The recognition rate is 94%.

References
  1. Bandara G. E, Pathirana S. D. , Ranawana R. M. 2002. Use of Fuzzy Feature Descriptions to Recognize Handwritten Alphanumeric Characters. In Proceedings of the 1st Conference on Fuzzy Systems and Knowledge Discovery, Singapore.
  2. Belal K. Elfarra and Ibrahim S. I. Abuhaiba. 2013. New Feature Extraction Method for Mammogram Computer Aided Diagnosis. International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 6, No. 1.
  3. Rajashekararadhya, S. and Ranjan, P. 2009. Zone based feature extraction algorithm for handwritten numeral recognition of kannada script. In proceedings of the Advance Computing Conference (IACC 2009). IEEE International, pages 525–528.
  4. L. M. Lorigo and V. Govindaraju. 2006. Offline Arabic handwriting recognition: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 5, pp. 712 - 724.
  5. Bandara G. E. , Pathirana S. D. , Ranawana R. M. 2002. A Short Method for On-line Alphanumeric Character Recognition. NAFIPS – FLINT 2002, New Orleans, USA.
  6. Pal, U. , Sharma, N. , Wakabayashi, T. , and Kimura, F. 2008. Handwritten character recognition of popular south indian scripts. In Doermann, D. and Jaeger, S. , editors, Arabic and Chinese Handwriting Recognition, volume 4768 of Lecture Notes in Computer Science, pages 251–264, Springer Berlin / Heidelberg.
  7. Jan J. 1998. Tutorial on fuzzy logic. Technical University of Denmark of Automation, Report No. 98-E868.
  8. Yadana T. and San S. Y. 2010. High Accuracy Myanmar Handwritten Character Recognition using Hybrid approach through MICR and Neural Network. International Journal of Computer Science Issues (IJCSI), Vol. 7, Issue 6.
  9. Muthumani . I , Uma Kumari C. R. 2012. Online Character Recognition of Handwritten Cursive Script. International Journal of Computer Science Issues (IJCSI), Vol. 9, Issue 3, No 2.
  10. Lauer, F. , Suen, C. Y. , and Bloch, G. 2007. A trainable feature extractor for handwritten digit recognition. Pattern Recognition, 40(6):1816–1824.
  11. Pal, U. , Sharma, N. , Wakabayashi, T. , and Kimura, F. 2008. Handwritten character recognition of popular south indian scripts. In Doermann, D. and Jaeger, S. , editors, Arabic and Chinese Handwriting Recognition, volume 4768 of Lecture Notes in Computer Science, pages 251–264, Springer Berlin / Heidelberg.
  12. Mahmood K Jasim, Anwar M Al-Saleh and Alaa Aljanaby. 2013. A Fuzzy Based Feature Extraction Approach for Handwritten Characters. International Journal of Computer Science Issues (IJCSI), Vol. 10, Issue 4, No 1.
Index Terms

Computer Science
Information Sciences

Keywords

Handwritten numeral recognition

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