Detection of Counterfeit Currency Notes Through Machine Learning Algorithms and Image Processing

In the modern financial sector, identifying fake money is a constant struggle. In order to address this issue, this research introduces a novel technique that correctly and quickly detects fake certifications by fusing machine learning methods with image processing. The suggested method trains a machine learning model with information from photos of actual and fake banknotes so that it can recognize the distinctive characteristics and patterns that separate real and fake banknotes. Additionally, different image processing techniques are employed to enhance image quality, lessen noise, and boost the clarity of crucial features. The efficiency of the procedure and accuracy in identifying fake goods were tested using the results. The proliferation of counterfeit certifications can be stopped, safeguarding the economy and boosting public confidence in the system, with the help of machine learning algorithms and machine images.elimination of fake credentials, safeguarding the economy and boosting public confidence in the system.