Our project aims to bridge this gap by introducing an inexpensive computer in the communication path so that the sign language can be automatically captured, recognized and translated to text for the benefit of deaf/dumb people. Hand signals must be analyzed and converted to textual display on the screen for the benefit of the hearing impaired. III. EXISTING METHODS The author Adithya published his paper “Artificial Neural Network based method for Indian Sign Language Recognition” on 2013 in IEEE Conference and he proposes that, “Sign Language is a language which uses hand gestures, facial expressions and body movements for communication. A sign language consists of either word level signs or finger spelling. It is the only communication mean for the deaf-dumb community. But the hearing people never try to learn the sign language. So the deaf people cannot interact with the normal people without a sign language interpreter. This causes the isolation of deaf people in the society. So a system that automatically recognizes the sign language is necessary. The implementation of such a system provides a platform for the interaction of hearing disabled people with the rest of the world without an interpreter. In this paper, we propose a method for the automatic recognition of finger spelling in Indian sign language