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B. El Kessab
Faculty of Science and Technology, BP 523, BeniMellal

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Isolated Handwritten Eastern Arabic Numerals Recognition Using Support Vectors Machines B. El Kessab; C. Daoui; B. Bouikhalene; R. Salouan
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp346-351

Abstract

In this paper, we present a comparison between the different variations of virtual retina (grid size) in features extraction with the support vectors machines classifier for isolated handwritten Eastern Arabic numerals recognition. For this purpose we have used for pre-processing each numeral image the median filter, the thresholding, normalization and the centering techniques. Furthermore, the experements results that we have obtained demonstrate really that the most powerful method is that virtual retina size equal 20x20. This work has achieved approximately 85% of success rate for Eastern Arabic numerals database identification.
Co-Authors B. Bouikhalene C. Daoui R. Salouan