Recognition of Persian Handwritten Digit using Fuzzy Logic

Recognition of Persian Handwritten Digit using Fuzzy Logic

Aminollah Mahabadi, Mohammad A. Torkamani, Majid Kazemian


Handwritten text recognition is one of the most interesting and open problems in optical character recognition. A variety of writing patterns, styles, and pen tips make this problem even more complicated. Using fuzzy logic techniques is shown to improve the performance of recognizing algorithm. In this research, a new fuzzy inference system for recognition of Persian-Arabic handwritten digits has been proposed. It is based on “line sweeping” of segmented image, which we called it hitcounting. The system extracts a digit from the input image, and finally recognizes the digit. The proposed system does not need any preprocessing algorithm like skeletonizing or contouring. It is also independent of thickness and size of pen while it is robust to small rotations. The implemented system could achieve 94.8% recognition on Persian-Arabic handwritten digits dataset as well as complete recognition for specific typefaces.


Persian-Arabic Handwritten Digit, Fuzzy Inference System, Pattern Recognition, Learning, Segmentation