User Identification Using HTK

As the rate of crime is increasing it is necessary to provide secure access for every individual. There are many methods for personal identification such as Smart cards, Personal identification number (PIN), Passwords. Though they provide secure access to authorized users, smart cards can be stolen, lost or duplicated while PIN and passwords can be forgotten, cracked. Forgery of signature can be done. But handwriting of every individual has unique characteristic. Hence it can be used to provide secure access. The main objective of this paper is to recognize cursive handwriting of a user by using Hidden Markov Model (HMM) with the help of HMM tool kit(HTK) in MATLAB. This Paper recognizes English handwritten scripts of 100 different users, where each user 9 instances are taken, in which some are kept separately for testing. By increasing the number of training instances, the rate of correct recognition goes on increasing.