Abstract—Recognition of Farsi/Persian handwritten numeral characters has been the focus of study recently and has many applications such as postal code reading and check processing. One important step in any recognition system is feature extraction. We propose to use a small set including only 20 domain specific features which are simple to understand, easy to implement and extracted in a way similar to how humans discriminate digits. These features are extracted by simply counting the pixels which are confined in different curves of digits. Unlike the universal methods this way of feature extraction is related to the problem. Evaluating the proposed features indicates an achievement of 97% recognition rate on Hoda dataset. This method is scale and shift invariant and no pre-processing is needed.

Index Terms—Persian handwritten digits, feature extraction,domain specific features.

The authors are with School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran (e-mail: Mirsharif@cse.shirazu.ac.ir,Mbadami@cse.shirazu.ac.ir,BaharSalehi@cse.shirazu.ac.ir, Azimifar@cse.shirazu.ac.ir)

Cite: G. Mirsharif, M. Badami, B. Salehi, and Z. Azimifar, "Recognition of Farsi Hand written Digits Using a Small Feature Set," International Journal of Computer and Electrical Engineering vol. 4, no. 4, pp. 588-591, 2012.