Offline Arabic Handwriting Identification Using Language Diacritics

In this paper, we present an approach for writer identification using off-line Arabic handwriting. The proposed method introduced Arabic writing in a new form, by presenting Arabic writing in its basic components instead of alphabetic. We split the input document into two parts: one for the letters and the other for the diacritics, we extract all diacritics from the input image and calculate the LBP histogram for each diacritic then concatenate these histograms to use it as handwriting features. We use the IFN/ENIT database in the experiments reported here and our tests involve 287 writers. The results show that our method is very effective and makes the handling of the Arabic handwriting more easily than before.