Online Arabic/Persian character recognition using neural network classifier and DCT features
Iman Khodadad, M.A. Sid-Ahmed, Esam Abdel‐Raheem · 2011
Online handwriting recognition is gaining interest due to the increase of pen computing applications and availability of tablet devices. The recognition of Arabic/Persian (A/P) characters is different from western handwriting, in which different calligraphic styles and cursive nature makes automatic recognition a more challenging and complicated task. In this paper, a new method is proposed to represent A/P characters. The proposed method incorporates a new set feature vectors suitable for A/P character set. A recognition system utilizing these set of features is developed for handwritten A/P characters. The result of the overall recognition system compare favorably with previous techniques.