Chinese Finger Alphabet Flow Recognition System Based on Data Glove
Yong Lin Lei · Jisuanji gongcheng · 2011
This paper studies the Chinese finger alphabet flow recognition and classification.As there is a problem that higher hardware requirements on data gloves are needed for the current study,a kind of lower hardware requirements and higher recognition rate method is proposed.This method uses BP neural network and Markov model and estimates the input sequence probability by Chinese alphabet spelling rules to output Chinese alphabet flow.Experimental results show that this method can get more than 91% recognition rate and output alphabet flow effectively,which proves the method is effective.