Farsi font recognition based on combination of Wavelet transform and Sobel-Robert operator features

In this paper, a new method for Farsi font recognition based on combination of features is proposed. The features are extracted and combined from textures of size 128×128 using SRF and Wavelet transform. Wavelet and SRF are naturally different methods of feature extraction, so their errors have low correlation. In this condition, the combination of these features which are both applicable for texture recognition was expected to reduce total error and the experimental results approved this hypothesis. The proposed algorithm is tested on 21000 samples provided from 10 common Farsi fonts. In the method presented here, the font characteristics are extracted well and this is clear in the results. We achieved the recognition rate of 95.56% using MLP classifier which is 2.37% and 11.79% more than SRF and Wavelet transform respectively.