A Comparative Study of Globally Popular Sign Language Recognition System

Sign language is an interaction method used by deaf and dumb people to exchange information between their community and other people. SLR (Sign Language Recognition) focuses on recognizing hand gestures and generating text for corresponding gestures. Both static and dynamic recognition are important for community communication. This paper reviews sign language techniques, focusing on hand segmentation and detection systems. It explores gesture taxonomies, representations, recognition algorithms, and software platforms. The review covers last few years of vision-based sign recognition algorithms, emphasizing their success in real-world applications. Sign language is a method, which is used to interact and create bridge among normal people who are not able listen hearing impaired. It involves gestures, such as rising eyebrows, shrugging shoulders, and shaking hands, which are movements of the body. SL is a structured way of interaction, assigning each word or alphabet to a gesture. There are number of SL in the world, including ISL stands for ISL, ASL, CSL, RSL, BSL, and JPL. SL uses face expressions, hand forms, and orientations to communicate. In Indian Sign Language, alphabets can be created using hand shapes, while some words or sentences require both hand shapes and facial expressions.