Recognition of Individual Handwritten Letters of the Farsi Language using a Decision Tree
Atefe MatinNiya, Hedieh Sajed · International Journal of Computer Applications · 2012
In this study, in order to recognize Farsi handwritten letters, firstthe pre-processing operation is done on the letters' images including normalization, thinning, reduction, noise reduction, etc.,and then the feature vector of the letters is extracted using the first to the forth momentums fromthe second level of wavelet transform and contourlettransform.A combination of decision-tree methods is used for the final recognition of letters.The database used in this study is the "Hoda" handwritten letter collection.The mean recognition rate in this combinational method is 97.89%.