Fake Currency Detection System

This project aims to develop a robust fake currency detection system leveraging image processing and machine learning techniques. Data cleaning involves image quality enhancement and handling of torn or dirty notes. The experimental setup includes a digital camera in a controlled lighting environment to capture currency images. MATLAB is used for software setup due to its extensive libraries. The algorithm involves pre-processing, feature extraction, and classification using machine learning algorithmslike decision trees or SVM. Continual model learning ensures adaptation to emerging counterfeit techniques. This system promises effective counterfeit detection with ongoing refinement, enhancing financial security.