Hand Posture to Text and its Implementation with Computer Vision

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Satabda Das, Pranab Hazra , Debanjana Chall , Subhadeep Karmakar, Spandan Sarkar, Swastika Dey, Ahana Chowdhury, Mitadru Mukherjee, Pankaj Ojha, Vishal Kumar Shaw, Nishant Minz

Abstract

One of the efficient ways of to avoid physical devices such as keyboards and mice are hand gesture controlled environment, where the user need to be located in a specific location to use these devices. The input feature plays a vital role in hand recognition, and the selection of good features representation. This paper deals with the hand posture and recognition method, as it is considered to be one of the challenging problem. Our main goal is to combine computer vision to our daily life to make optimal use of it. Some of the applications and system based on hand posture recognition are discussed in the explanation section hope it would help in succeeding the goal of this research area. In case of this we have tried to implement deep learning method called as convolution neural network(CNN) to make this project be more fruitful.

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