A hybrid approach for multifont Arabic characters recognition
Nadia Ben Amor, Najoua Essoukri Ben Amara · 2006
Abstract: Pattern recognition is a well-established field of study and Optical Character Recognition (OCR) has long been seen as one of its important contributions. In this paper we describe the performances of a hybrid classification approach which combines both neural networks and hidden Markov models. This classification technique is dealing with features extracted through the wavelet transform method. Experimental tests have been carried out on a set of 85.000 samples of characters corresponding to 5 different Arabic fonts. Some promising experimental results are reported.