Off-Line Writer Recognition for Farsi Text
Ali Rafiee, Hamidreza Motavalli · 2007
A new off-line writer recognition method for Farsi text is presented in this paper. 8 different types of features obtained from the handwritten line of text were considered to identify writers based on theirs handwritten. These features are associated with height and width of text. A typical feed forward neural network was used for classification. This method was applied to 20 writers who wrote 5 to 7 lines and 86.5% recognition rate was obtained.