Automatic Indian Sign Language recognition system

Sign Language is the most natural and expressive way for the hearing impaired. This paper presents a methodology which recognizes the Indian Sign Language (ISL) and translates into a normal text. The methodology consists of three stages, namely a training phase, a testing phase and a recognition phase. Combinational parameters of Hu invariant moment and structural shape descriptors are created to form a new feature vector to recognize sign. A multi-class Support Vector Machine (MSVM) is used for training and recognizing signs of ISL. The effectiveness of the proposed method is validated on a dataset having 720 images. Experimental results demonstrate that the proposed system can successfully recognize hand gesture with 96% recognition rate.