Handwritten Arabic character recognition based on SVM Classifier

This paper describes new methods for handwritten Arabic character recognition. We propose a novel algorithm for smoothing image and segmentation of the Arabic character using width writing estimated from skeleton character. The moments and Fourier descriptor of profile projection and centroid distance are used as features of each character these feature are invariant in translation , rotation and scale we apply Principal component Analysis (PCA) as data processing algorithm to features vector in order to reduce dimension. The classifier proposed in this work is based on Support Vector Machines (SVM) wich considerd an recent optimal classifier up to now. The results show that these methods are very powerful for isolated handwritten Arabic character.