REAL TIME HAND GESTURE RECOGNITION AND VOICE CONVERSION SYSTEM FOR DEAF AND DUMB PERSON BASED ON IMAGE PROCESSING

Abstract

Communication between normal and handicapped person such as deaf people, dumb people, and blind people has always been a challenging task. It has been observed that they find it really difficult at times to interact with normal people with their gestures, as only a very few of those are recognized by most people. Since people with hearing impairment or deaf people cannot talk like normal people so they have to depend on some sort of visual communication in most of the time. Sign Language is the primary means of communication in the deaf and dumb community. As like any other language it has also got grammar and vocabulary but uses visual modality for exchanging information. The importance of sign language is emphasized by the growing public approval and funds for international project. Interesting technologies are being developed for speech recognition but no real commercial product for sign recognition is actually there in the current market. So, to take this field of research to another higher level this project was studied and carried out. The basic objective of this research is to develop MATLAB based real time system for hand gesture recognition which recognize hand gestures, features of hands such as centroid, peak calculation, angle calculation and convert gesture images into voice and vice versa. To implement this system we used simple night vision web-cam with 20 megapixel intensity. The idea consisted of designing and building up an intelligent system using image processing, data mining and artificial intelligence concepts to take visual inputs of sign languages hand gestures and generate easily recognizable form of outputs in the form of text and voice with 82% accuracy.