A Novel Signature Verification Based Automatic Teller Machine
Keywords:
Continuous dynamic time wraping, dynamic time wraping, hidden markov model, automatic teller machine, unique identity numberAbstract
Biometric identification is the need of hour and
automatic recognition systems are such biometric techniques to look upon. Accurate automatic recognition systems are important for a wide range of applications such as banks, restricted areas, government classified areas etc. As traditional
identity recognition methods such as pins, passwords etc suffer from some fattle flaws and are unable to satisfy the security requirements. The paper introduces a novel system, a combination of behavioral traits as well as traditional methods for identity recognition. The system uses signature verification as the behavioral trait along with an unique identity number (referred as UIN in rest of paper) for the recognition. Signature verification is an important domain for confirming a person’s identity. The system is applied of an ATM (Automatic Teller Machine) to decrease the risk of theft from an individual’s account. It can be effectively employed to reduce the risk of forgery by releasing the trouble of carrying ATM cards by the users, by employing a signature verification system fused with
an unique identity number. The paper further presents a comparison of three extremely efficient methods CDTW (Continuous Dynamic Time Warping), DTW (Dynamic Time Wraping) and HMM (Hidden Markov Model) employed for signature verification and the best method was stated.
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