NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 2, ISSUE 9, September -2016 39 | Page REAL TIME HAND GESTURE RECOGNITION AND VOICE CONVERSION SYSTEM FOR DEAF AND DUMB PERSON BASED ON IMAGE PROCESSING SHWETA SONAJIRAO SHINDE M.E Student. Electronics and Telecommunication Department, Deogiri Institute of Engineering and Management Studies, Aurangabad (MS), India Dr. R.M. AUTEE H.O.D. Electronics and Telecommunication Department, Deogiri Institute of Engineering and Management Studies, Aurangabad (MS), India 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. KEYWORDS: hand gesture recognition, voice conversion, gesture to speech, speech to gesture conversion. I. INTRODUCTION: One of the important problems that our society faces is that people with disabilities are finding it hard to come up with the fast growing technology. In the recent years, there has been a rapid increase in the number of hearing impaired and speech disabled victims due to birth defects, oral diseases and accidents. When a deaf-dumb person speaks to a normal person, the normal person seldom understands and asks the deaf-dumb person to show gestures for his/her needs. Dumb persons have their own language to communicate with us; the only thing is that we need to understand their language. Generally dumb people use sign language for communication but they find difficulty in communicating with others who don’t understand sign language. For better communication between deaf and normal people we proposed a system which converts gesture images into speech and vice versa. The sign language translation system translates the normal sign language to speech and hence makes the communication between normal person and dumb people easier. Many research works related to Sign languages have been done as for example the American Sign Language, the British Sign Language, the Japanese Sign Language, and so on. Finding an experienced and qualified interpreters every time is a very difficult task and also unaffordable. Automated speech recognition system which aims to convert the speech signals into text form. Hence the two way communication is possible between deaf-mute person and normal person. Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate