International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2557

Full Length Research Paper

Farsi digit recognition via features extraction

Mehdi Alirezanejad and Rasul Enayatifar*
  Islamic Azad University, Firuzkooh Branch, Firuzkooh, Iran.
Email: [email protected]

  •  Accepted: 14 March 2011
  •  Published: 31 July 2011



In this paper, a new method is proposed to extract the features of a one-number Persian image in which for the final verification of the extracted features, a three-layer neural network (mesh) of Perceptron has been utilized. The method is capable of extracting some ideal features from a one-number image that are stable against rotation, movement, size change and noise. The method is examined on a database of 60000 discredited numbers, from which 40000 numbers were used in the training stage and 20000 ones were used for the experiment. The recognition percentage of 92.7% shows the great efficiency of the proposed method.


Key words: Features extraction, recognition of Persian numbers, perceptron neural network, standard deviance, average angle.