Sign Language Recognition using Sensor and Vision Based Approach

Sign language is one of mode for Communication which conveys the ideas non-verbally. It is gift for speech and hear impaired community. A Sign Language Recognition system has made this community close to regular communication. This system convert's the signs or gestures to a form which is easily understood. System is trained by using images of letters. As technology improved many different methods have evolved to create this system. In this study, two main methods for implementing sign language recognition are i) Sensor-based approach ii) Vision-based approach are studied. In image-based, cameras are used to capture the images of signs and use image processing to identify the sign in image and then algorithm that interpret the meaning of that sign. The sensor-based approach a glove is constructed using sensors that will track the sign made by hand. In this paper translation of sign to speech, methods to SLR, sign language interpretation, techniques to map features and popular methods are studied.