A Comparative Study on Sign Language Recognition Methods

Abstract

The process by which two or more people exchange their information, views, and opinions on different situations and on different topics is known as communication. The need for a common platform for humans to communicate with one another has played an essential role in the evolution of human civilization ever since its start. Human beings communicate with each other using several verbal and non-verbal cues. Non-verbal communication involves the use of signs and hand gestures. Hard-of-hearing individuals can communicate only using non-verbal cues and they rely on others to communicate with them using hand gestures as well. Systematic sign language systems, for instance, the American Sign Language, the Indian Sign Language and several such similar sign language systems have been developed to aid the specially abled individuals. Sign Language recognition (SLR) is a process that uses technology to recognize what the specially-abled person is saying by identifying the signs and hand gestures and returning the output in the form of text or speech. In this survey, a comparative analysis is done based on the various techniques and algorithms used and implemented to carry out the process of Sign language Recognition (SLR).