Identification of Counterfeit Currency for Visually Impaired People using Hybrid Model

Counterfeit currency detection is a significant challenge for visually impaired individuals. This project proposes a hybrid model that combines image processing and machine learning techniques to assist in identifying fake currency. The system uses a ML Algorithms to classify notes as genuine or counterfeit by analyzing security features such as watermarks and holograms. Designed for accessibility, it provides result via audio, allowing visually impaired users to verify currency easily and accurately. The solution is portable, cost-effective, and enhances financial independence for visually impaired individuals.