Printed Arabic Characters Recognition Based on Minimum Distance Classifier Technique


The printed Arabic character recognition are faced numerous challenges due to its character body which are changed depending on its position in any sentence (at beginning or in the middle or in the end of the word). This paper portrays recognition strategies. These strategies depend on new pre-processing processes, extraction the structural and numerical features to build databases for printed alphabetical Arabic characters. The database information that obtained from features extracted was applied in recognition stage. Minimum Distance Classifier technique (MDC) was used to classify and train the classes of characters. The procedure of one character against all characters (OAA) was used in determining the rate of recognition. The suggested approaches have yielded unique and encouraging results in terms of accuracy in which the recognition rate reached to 97.28%. These approaches are faster and more efficient than other methods.