Nowadays, the prevalence of counterfeit money has grown dramatically, which has prompted researchers to look into digital imaging methods for detecting genuine currency or counterfeit cash. One of the qualities of printers whose ink is extremely good and can print money like the original makes the layperson more apprehensive of money ownership because of the technological sophistication of the printer. KNN (K-Nearest Neighbor) and CNN were used in this study to verify the currency's legitimacy (Convolutional Neural Network). The KNN algorithm has an accuracy rate of 87,75 percent. While CNN uses a detection accuracy of 96,67%. Pre-production on the set and the image utilised can help improve the results of these two procedures, as can sophisticated study. The same exposure level, image capture angle, and image size are used in the data set.

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