Real-Time Identification of Fake Currency Notes Using YOLOv9 and GELAN

In the past many years, counterfeit currency has been proliferating on a large scale in India, which is not just increasing black money but also destroying the value and reputation of Indian currency in the global market. The actual circulation of counterfeit notes across India remains unknown, posing a significant threat to the financial security of ordinary citizen. Hence, this research proposes utilizing YOLOv9 technology, a real time advanced object detection model, to develop a machine-learning system for detecting counterfeit Indian currency. Here we are focusing on the Rs 500 note, and using its images, we are creating a robust model to detect fake currency by training the model with both real and fake denominations of Rs 500. In this, we are using the latest version of YOLO, which is v9, and its latest technology, GELAN, which improves the accuracy and efficiency of the model to detect the fake currency notes from the real one using image processing Techniques.