HANDWRITING IDENTIFICATION USING ANFIS (JOURNAL OF SOCIAL SCIENCE RESEARCH, 2014)
A new method for handwriting identification was presented.Individual characters was separated from a word choosed from a paragraph of handwritten text image which is given as input to the system. Then each of the separated characters are converted into column vectors of 625 values that are later fed into the adaptive neural fuzzy inference system(ANFIS), which was calculate membership function(MF) and normalized firing strength.In our paper we were used triangular membership function and compare with others MF.The networks has been designed with single layered neural network corresponding to a character from a-z, the outputs of all the column vector is fed into network the which has been developed using the concepts of correlation, with the help of this the overall network is optimized with the help of column vector thus providing us with recognized outputs with great efficiency.