Smart Currency Authentication: Real-Time Fake Note Detection Using CNN and Flask

Abstract

Counterfeit currency has become a significant problem affecting financial institutions, businesses,
and individuals worldwide. Fake currency circulation can cause economic instability and financial losses.
Traditional manual detection methods are often inefficient and require trained personnel. Therefore, an
automated system for currency authentication is essential. This project proposes a Smart Currency
Authentication System that detects counterfeit currency in real time using Deep Learning techniques,
specifically Convolutional Neural Networks (CNN). The system analyzes currency note images captured
through a camera or uploaded by the user and identifies whether the note is genuine or fake based on trained
patterns and security features.