International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Identifying and Detecting Currency through Image Processing with Convolutional Neural Network

Moksud Alam MallikDean R&D, Associate Professor, Department of CSE (Data Science), Lords Institute of Engineering and Technology, Hyderabad, IndiaMohammed Abdul MubashirUG Student, Department of CSE (Data Science), Lords Institute of Engineering and Technology, Hyderabad, IndiaSameena SultanaUG Student, Department of CSE (Data Science), Lords Institute of Engineering and Technology, Hyderabad, IndiaMirza Younus Ali BaigAssistant Professor, Department of CSE (Data Science), Lords Institute of Engineering and Technology, Hyderabad, IndiaMd Ashique HussainAssistant Professor, Department of CSE (Data Science), Lords Institute of Engineering and Technology, Hyderabad, India

Vol 9 No 25 (2025): Volume 9, Special Issue of INSPIRE’25 April 2025 | Pages: 328-336

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 24-04-2025

doi Logo doi.org/10.47001/IRJIET/2025.INSPIRE53

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Abstract

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%.

Keywords

Currency Recognition, Image Processing, Convolutional Neural Network (CNN), Automated Detection, Digital Image Analysis


Citation of this Article

Moksud Alam Mallik, Mohammed Abdul Mubashir, Sameena Sultana, Mirza Younus Ali Baig, & Md Ashique Hussain. (2025). Identifying and Detecting Currency through Image Processing with Convolutional Neural Network. In proceeding of International Conference on Sustainable Practices and Innovations in Research and Engineering (INSPIRE'25), published by IRJIET, Volume 9, Special Issue of INSPIRE’25, pp 328-336. Article DOI https://doi.org/10.47001/IRJIET/2025.INSPIRE53

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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