Real Time Face Detection and Pin Authentication for ATM Machine

Abstract

With the increasing incidence of ATM fraud, there is a pressing need for enhanced security measures in automated teller machines (ATMs). This paper presents a dual-factor authentication system that integrates face recognition and Personal Identification Number (PIN) verification to improve ATM transaction security. Utilizing a Convolutional Neural Network (CNN) for real-time face recognition, the proposed system significantly reduces the risk of unauthorized access. The implementation includes an Arduino-based cash dispenser and a web application developed using Tkinter, demonstrating a robust prototype that effectively mitigates ATM fraud.