Recognition of Off-line Printed Arabic Text Using Hidden Markov Models - Sabih Shaker, Atheel (Ibn AL-Haitham Journal For Pure and Applied Sciences, 2018)
In this paper, we introduce a method to identify the text printed in Arabic, since the recognition of the printed text is very important in the applications of information technology, the Arabic language is among a group of languages with related characters such as the language of Urdu , Kurdish language , Persian language also the old Turkish language " Ottoman ", it is difficult to identify the related letter because it is in several cases, such as the beginning of the word has a shape and center of the word has a shape and the last word also has a form, either texts in languages where the characters are not connected, then the image of the letter one in any location in the word has been Adoption of programs ready for him A long time. In this paper we present an off-line system to recognize printed Arabic text by using Hidden Markov Model with the aid of algorithm that segment the text line into sections and then into characters.