Classification Approach for Sign Language Recognition

Srinath, Ganesh Sharma
In recent years, a lot of research is being done in the field of Computer Vision and Human Computer Interaction where hand gestures play a vital role. Hand gestures or Hand signs are more powerful means of communication for hearing impaired people when they communicate to the normal people everywhere in day to day life. As the normal people find it difficult to interpret the meaning of sign language expressed by the hearing impaired, it is inevitable to have an interpreter for recognizing and
more » ... anslating the sign language. Computer recognition of sign language is an important research problem for enabling communication with hearing impaired people. This paper introduces a classification approach for recognizing and translating the static alphabets of American Sign Language (ASL). The images representing the alphabets are the input for the system which is obtained using digital camera. The output is the corresponding alphabet in the textual form. As the ASL uses only the palm for represent the alphabets, Segmentation technique is applied to the input image to obtain the palm and it is further processed using classification approach to recognize and translate them. This approach yields a success rate of 86.67%.