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Sign Language to Number by Neural Network

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Executive Summary

In this paper is presented an automatic deaf language to number recognition system. Sign language number recognition system lays down foundation for hand shape recognition which addresses real and current problems in signing in the deaf community and leads to practical applications. The scheme is based on Neural Network (NN) classifier using a back propagation. The input for the sign language number recognition system is 1000 Indian Sign Language number images with 640 x 480 pixels size. The input parameter vector to neural network is the Fisher score, which represents the derivate of the matrix of symbol probability in Hidden Markov Model (HMM). The HMM, which needs a sequence to be trained and used, is fed by the hand contour chain code.

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