Recognition and Translation of Hand Gestures to Urdu Alphabets Using a Geometrical Classification

Abstract

Recognition of hand gestures associated with different alphabets is a very important research area. The persons with vocal and hearing disabilities may benefit a lot from this research. The communication gap between these and normal persons can be filled by providing an aid in the form of a computerized translation of different hand gestures. In this paper, we have developed a recognition system to translate hand gestures into Urdu alphabets. We have formulated a comprehensive classification scheme which is core to this recognition system. The accuracy rate of our approach is 97.4% which is better than the previous approaches.