Offline Isolated Arabic Handwriting Character Recognition System Based on SVM

This paper proposed a new architecture for Offline Isolated Arabic Handwriting Character Recognition System Based on SVM (OIAHCR). An Arabic handwriting dataset also proposed for training and testing the proposed system. Although half of the dataset used for training the Support Vector Machine (SVM) and the second half used for testing, the system achieved high performance with less training data. Besides, the system achieved best recognition accuracy 99.64% based on several feature extraction methods and SVM classifier. Experimental results show that the linear kernel of SVM is convergent and more accurate for recognition than other SVM kernels.