Enhanced Security Feature of ATM's Through Facial Recognition

Automated Teller Machines also known as ATM's are widely used nowadays by each and everyone. The ATM machine (Automated Teller Machine) is an electronic device that is used by the banks to perform banking tasks like withdrawal of money, transferring of money, and many to get many information about a user's bank account without the need to visit a bank. This System revolutionised the way of transactions. There were no long lines of queue in front of the bank for a simple withdrawal of money. The number of ATM's a bank has can be a factor in considering the strength of a bank. As there is increase in the number of ATM's, there is also increase in the fraudulent activities in the ATM. The main motivation of this project is to increase the security feature of the use of ATM. The current method uses static key (PIN) for security. The proposed method uses Face-id as a key incorporated with current method. The advantages can be found as that the face-id is unique for everybody; it cannot be used by anybody other than the user. For the implementation of the face-id scan, the machine learning and image processing algorithms (Eigenface algorithm) are used.