A Novel Approach to Low Cost Multi Language Speaker Sign Recognition System

This work proposed a comprehensive approach for the recognition of speaker in multi Indian languages. The Objective of this work is to recognize the hand gesture using several combinations of techniques. Hand gestures are a potential symbolic representation for many applications including health care, virtual reality and human-robot interaction. Hand gestures play a vital role for transfering the information and emotions among each other. As the hand gestures are the outcome of the body movement, it is refered as dynamic hand gesture. So it is very important to track and identify the motion of hand to offer versatile use. Recognition of American Sign Language (ASL) from the video stream consists of three main parts as Image procurement, feature extraction and gesture allocation. Investigational outcomes demonstrate that the proposed approach can effectively identify the key hand gestures with greater accuracy rate and work very well in intricate situation.