Sign Language Recognition System Mayuresh Keni 1 , Shireen Meher 2 , Aniket Marathe 3 , Prof. Amruta Chintawar 4 , Prof. Shweta Ashtekar 5 Department of Electronics Engineering Ramrao Adik Institute of Technology Dr. D.Y. Patil Vidyanagar Nerul, Navi Mumbai-400706 1 mayureshkeni1004@gmail.com, 2 shireenmk@gmail.com , 3 aniket.marathe16@gmail.com , 4 amrutachintawar239@gmail.com Abstract— The only way the speech and hearing impaired (i.e dumb and deaf) people can communicate is by sign language. The main problem of this way of communication is normal people who cannot understand sign language can’t communicate with these people or vice versa. Our project aims to bridge the gap between the speech and hearing impaired people and the normal people. The basic idea of this project is to make a system using which dumb people can significantly communicate with all other people using their normal gestures. The system does not require the background to be perfectly black. It works on any background. The project uses image processing system to identify, especially English alphabetic sign language used by the deaf people to communicate and converts them into text so that normal people can understand. I. INTRODUCTION Dumb people are usually deprived of normal communication with other people in the society. Also normal people find it difficult to understand and communicate with them. These people have to rely on an interpreter or on some sort of visual communication. An interpreter won’t be always available and visual communication is mostly difficult to understand. Sign Language is the primary means of communication in the deaf and dumb community. As a normal person is unaware of the grammar or meaning of various gestures that are part of a sign language, it is primarily limited to their families and/or deaf and dumb community. At this age of technology, it is quintessential to make these people feel part of the society by helping them communicate smoothly. Hence, an intelligent computer system is required to be developed and be taught. Researchers have been attacking the problem for quite some time now and the results are showing some promise. Interesting technologies are being developed for speech recognition but no real commercial product for sign recognition is actually there in the current market. II. LITERATURE SURVEY The researches done in this field are mostly done using a glove based system. In the glove based system, sensors such as potentiometer, accelerometer etc. is attached to each of the finger. Based on their readings the corresponding alphabet is displayed. Christopher Lee and Yangsheng Xu developed a glove-based gesture recognition system that was able to recognize 14 of the letters from the hand alphabet, learn new gestures and able to update the model of each gesture in the system in online mode. Over the years advanced glove devices have been designed such as the Sayre Glove, Dexterous Hand Master and Power Glove. The main problem faced by this gloved based system is that it has to be recalibrate every time whenever a new user uses this system. Also the connecting wires restrict the freedom of movement. This system was also implemented by using Image Processing. In this way of implementation the sign language recognition part was done by Image Processing instead of using Gloves. But the only problem this system had was the background was compulsorily to be black otherwise this system would not work. Also some of the systems required color bands which were meant to be wore on the finger-tips so that the fingerstips are identified by the Image Processing unit. We are implementing our project by using Image Processing. The main advantage of our project is that it is not restricted to be used with black background. It can use with any background. Also wearing of color bands is not required in our system. III. PROPOSED METHODOLOGY In this paper we would present a robust and efficient method of sign language detection. Instead of using Datagloves for sign language detection, we would be doing the detection by image processing. The main advantage of using image processing over Datagloves is that the system is not required to be 270 International Journal of Engineering Research & Technology (IJERT) www.ijert.org ICONECT' 14 Conference Proceedings