1 College of Engineering,University of Karbala, Karbala, Iraq

2 Department of Electrical Engineering, University of Technology, Baghdad, Iraq


The recognition and classification of languages represent a vital factor in the
computer interaction. This paper presents Arabic Sign Language recognition, which is
represented as an appealing application. The work in this paper is based on three steps;
preprocessing, feature extraction and classification (Recognition). The statistical features
have been used than the physical features, while Multilayer feed-forward neural network
as classification methods. The recognition percent is 96.33% has been gained over-perform
the earlier works. The simulation has been made by using Matlab 2015b.