Identification of Counterfeit Currency Using Image Processing and Deep Learning

Nowadays, The increase of counterfeit (Fake or Forgery) currency poses a significant threat to financial systems and undermines trust in monetary transactions. This research addresses the challenge of fake currency detection by leveraging the power of deep learning, specifically Convolutional Neural Networks (CNN), in conjunction with advanced image processing techniques. The proposed system aims to enhance the accuracy and efficiency of counterfeit currency detection through the automated analysis of currency images. The study begins with a comprehensive dataset comprising genuine and counterfeit currency images, ensuring a diverse representation of various denominations and currencies. The integration of deep learning and image processing techniques provides a comprehensive and automated means to combat the growing threat of fake currency in today’s dynamic financial landscape. In the relentless pursuit of financial security, our approach not only identifies counterfeit currency but stands resilient against evolving fraudulent tactics. The fusion of Convolutional Neural Networks and advanced image processing techniques not only ensures accuracy but also adaptability to new challenges.