Abstract
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.
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More From: Iraqi Journal of Computer, Communication, Control and System Engineering
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