Abstract: Generally hearing impaired people use sign language for communication, but they find difficulty in communicating with others who don’t understand sign language. This project aims to lower this barrier in communication. It is based on the need of developing an electronic device that can translate sign language into text in order to make the communication take place between the mute communities and the general public as possible. Computer recognition of sign language is an important research problem for enabling communication with hearing impaired people. This project introduces an efficient and fast algorithm for identification of the number of fingers opened in a gesture representing text of the Binary Sign Language. The system does not require the hand to be perfectly aligned to the camera and any specific back ground for camera. The project uses image processing system to identify, especially English alphabetic sign language used by the deaf people to communicate. The basic objective of this project is to develop a computer based intelligent system that will enable the hearing impaired significantly to communicate with others using their natural hand gestures. The idea consisted of designing and building up an intelligent system using image processing, machine learning and artificial intelligence concepts to take visual inputs of sign language’s hand gestures and generate easily recognizable form of outputs. Hence the objective of this project is to develop an intelligent system which can act as a translator between the sign language and the spoken language dynamically and can make the communication between people with hearing impairment and normal people both effective and efficient. The system is we are implementing for Binary sign language but it can detect any sign language with prior image processing.
Keywords: Image Processing, Sign language, Pattern Reorganization, Colour Detection, Shape Detection, Text Generation, Open CV, C++.