JOURNAL OF MULTIMEDIA (JMM)
ISSN : 1796-2048
Volume : 1    Issue : 2    Date : May 2006

Multifont Arabic Characters Recognition Using HoughTransform and HMM/ANN Classification
Nadia Ben Amor and Najoua Essoukri Ben Amara
Page(s): 50-54
Full Text:
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Abstract
Optical Characters Recognition (OCR) has been an active subject of research since the early days of
computers. Despite the age of the subject, it remains one of the most challenging and exciting
areas of research in computer science. In recent years it has grown into a mature discipline,
producing a huge body of work. Arabic character recognition has been one of the last major
languages to receive attention. This is due, in part, to the cursive nature of the task since even
printed Arabic characters are in cursive form.
This paper describes the performance of combining Hough transform and Hidden Markov Models in
a multifont Arabic OCR system. Experimental tests have been carried out on a set of 85.000
samples of characters corresponding to 5 different fonts from the most commonly used in Arabic
writing. Some promising experimental results are reported.

Index Terms
Arabic Optical Character Recognition, Hough Transforms, Hidden Markov Models, Artificial Neural
Networks