SIGN LANGUAGE USING TENSOR FLOW

Abstract

Inability to speak is considered a serious disability. People with this disability use different modes to communicate with others. There are number of methods available for their communication, one such common method of communication is sign language. Hand motion is the strategy utilized in gesture-based communication for non-verbal correspondence. It is generally utilized by hard of hearing and moronic individuals who have hearing or discourse issues to impart among themselves. Numerous producers around the globe have developed different communications using gesture frameworks. However, they are neither adaptable nor practical for the end clients. Henceforth in this paper presented programming which displays a framework model that can consequently perceive gesture based communication to help hard of hearing and unable to speak individuals to impart all the more viably with one another or typical individuals. Example acknowledgment and Gesture acknowledgment are the creating fields of research. Being a huge part in nonverbal correspondence hand signals are assuming key job in our daily life. Hand Gesture acknowledgment framework gives us an imaginative, common, easy to use method for correspondence with the PC which is increasingly recognizable to the individuals. By considering at the top of the priority list, the likenesses of human hand shape with four fingers and one thumb. The product expects to introduce a continuous framework for acknowledgment of hand motion on premise of location of some shape based highlights like introduction, centre of mass (centroid), fingers status, thumb in places of raised or collapsed fingers of hand. Developing sign language application for deaf people could be very important, as they will be able to communicate easily with even those who do not understand sign language. Our project aims at taking the basic step in bridging the communication gap between normal people, deaf and dumb people using sign language. The focus of this work is to create a vision base system to identify sign language gestures from the video sequences. The reason for choosing a system based on vision relates to the fact that it provides a simpler and more intuitive way of communication between a human and a computer.