Classifying of Isolated Handwritten Arabic Characters (on-line) Using Machine Learning Methods
DOI:
https://doi.org/10.54388/jkues.v3i1.251Keywords:
Online Arabic handwriting, Isolated characters, Machine learning, Classification methodsAbstract
The prediction of Arabic handwritten characters is one of the fascinating matters in the area of artificial intelligence (AI) and machine learning, especially in the case of on-line handwriting. In the handwriting recognition system, characters are classified according to their particular categories by utilizing -as input- the values of the features extracted from them. Our major objective in this paper is to classify the isolated characters for online Arabic handwriting (? to ?) using machine learning techniques with the features from EDMs (Edge Direction Matrixes) as opposed to EEDMs (Extended Edge Direction Matrixes). With respect to all classification methods used in this study, EEDMs with machine learning techniques had better performance than EDMs in recognizing isolated Arabic online characters.
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