Multifont Arabic Characters Recognition Using HoughTransform and HMM/ANN Classification

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.

• Type: Journal
• Year: 2006
• Where: JMM2
• Authors: Nadia Ben Amor, Najoua Essoukri Ben Amara
• Keywords: Arabic Character Recognition, Arabic Characters, JMM2 2006, Multifont Arabic Ocr