Sign Language is the language used by the deaf and dumb people to communicate. However, this language is rarely learnt by the general public. So it becomes difficult for these people to communicate with the general masses. Various such methods and techniques have been developed for the American Sign Language. This paper proposes an interpretation technique for the Indian Sign Language which is equally complex in nature and uses various parts of the body to convey messages such as hand orientations, palm movement, fingertips, etc. Our proposed technique will be able to take in a live video stream consisting of gestures and convert it into an equivalent sentence in English. The solution offered consists of steps like frame extraction, segmentation and refining of images, feature extraction, and training of neural network. The various methods will have different accuracy and efficiency levels and thus training of the network to perfectly guess each sign is of utmost importance.

Neural Networks, Video Processing, Indian Sign Language

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