A Robust Framework for Counterfeit Currency Detection Using CNN

Abstract

Fake currency circulation is a serious issue that affects the economic stability of many countries, including India. Traditional methods of currency verification based on manual inspection and basic machine learning techniques often suffer from low accuracy and inefficiency in detecting advanced counterfeit notes. In this paper, a deep learning-based approach using Convolutional Neural Networks (CNN) is proposed for the automatic detection of fake currency through image processing. The system extracts important visual features such as texture, patterns, and security elements from currency note images and classifies them as genuine or counterfeit. The proposed model improves detection accuracy and provides faster results compared to existing systems. Experimental results demonstrate that the system achieves high accuracy and can be effectively used for real-time currency authentication in practical applications.