Recognition of off-line printed arabic text using hidden markov models

• Published in: Ibn Al-Haitham Journal for Pure and Applied Sciences Vol. 31; no. 2; pp. 230 - 238
• Main Author: Shakir, Athil Subayh
• Format: Journal Article
• Language: English
• Published: Baghdad, Iraq University of Baghdad, College of Education for Pure Science / Ibn al-Haitham 12-09-2018; University of Baghdad
• Subjects: Automatic identification, Hidden Markov series, Printed text, Automatic recognition of printed text, Markov series automatic recognition
• DOI: 10.30526/31.2.1952
• EISSN: 2521-3407
• ISSN: 1609-4042

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.