Identifying and Detecting Currency through Image Processing with Convolutional Neural Network
Moksud Alam Mallik, Mohammed Abdul Mubashir, Sameena Sultana, Mirza Younus Ali Baig, Md Ashique Hussain · International Research Journal of Innovations in Engineering and Technology · 2025
Bank currency is our nation's most valuable asset, and in order to cause financial inconsistencies, counterfeit notes that seem like the real thing are introduced into the financial market. During demonetization time it is seen that so much of currency is floating in market. In general, by a human being, it is very difficult to identify forged note from the genuine not instead of various parameters designed for identification as many features of forged note are similar to original one. To discriminate between fake bank currency and original note is a challenging task. So, there must be an automated system that will be available in banks or in ATM machines. To design such an automated system there is need to design an efficient algorithm which is able to predict weather the banknote is genuine or forged bank currency as fake notes are designed with high precision. This paper proposes a CNN algorithm-based fake currency detection model for authenticating Indian currency notes with denominations of 10, 20, 50, 200, and 500. The results are also fairly good and also proposed model has the accuracy of 99.3%.