Enhancing Currency Authentication: A Machine Learning Framework for Detecting Counterfeit Banknotes

Counterfeiting of currency poses a significant threat to individuals and the national economy. While fake currency detectors exist, they are mostly limited to banks and corporate offices, leaving common people and small businesses vulnerable. To address this issue, our project focuses on developing a software-based currency authentication system using advanced image processing and computer vision techniques. By analyzing key security features of Indian currency, we aim to create a robust detection model that can accurately identify counterfeit notes. The system is designed entirely in Python within the Jupyter Notebook environment, leveraging machine learning and deep learning algorithms for enhanced accuracy. This solution provides an accessible, costeffective, and scalable approach to counterfeit detection, empowering individuals and small businesses to verify currency authenticity efficiently. Our project contributes to financial security and fraud prevention, ensuring greater trust in daily monetary transactions.