Offline Isolated Arabic Handwriting Character
Recognition System Based on SVM
Mustafa Salam1 and
Alia Abdul Hassan2
1Computer Engineering Techniques, Imam Ja'afar Al-Sadiq
University, Iraq
2Computer
Science Department, University of Technology, Iraq
Abstract: 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.
Keywords: Arabic character, pre-processing, feature
extraction, classification.