Counterfeit Currency Detection using Machine Vision and Image Processing

The widespread use of fake goods and money in international trade presents a serious problem that calls for the creation of sophisticated detection methods and automated solutions. The potential financial losses and security hazards connected with counterfeiting are the driving forces behind this issue's resolution. Despite current detection techniques, they still require improvement in terms of accuracy and efficiency. To improve counterfeit identification, the proposed method makes use of classifiers and a variety of image processing techniques. Possible problems with a false currency identification were included to a customised dataset. The suggested approach shows its efficacy in enhancing detecting skills with an impressive 96% accuracy rate. The results of the study demonstrate how automated image analysis methods can improve counterfeit identification and lay the groundwork for further research in this area.