Persian Character Recognition Using New Hybridization of Independent Orthogonal Moments
نویسنده
چکیده
Character recognition is a new research field in the domain of pattern recognition which deals with the style of writing. Some of the challengeable problems in character identification are changing in the style of writing, font and turns of words and etc. In this paper, the goal is Persian character identification using independent orthogonal moment as the feature extraction technique.The proposed feature extraction method is the combination of Pseudo-Zernike Moment and Fourier-Mellin Moment called Pseudo-ZernikeMellin Moment to extract feature vector from Persian characters. The proposed character identification system is evaluated on the HODA dataset and obtained 97.76% acceptance rate.
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