Fake Currency Detection Using Convolutional Neural Network and Textual Feature Analysis

DOI

10.2991/978-94-6463-866-0_71How to use a DOI?

Keywords

Fake Currency; CNN; OCR; Indian Banknotes; Deep Learning; Hybrid Detection

Abstract

Counterfeit money is a serious threat to economic stability and public confidence. This paper introduces an integrated Fake Currency Detection System based on Convolutional Neural Networks (CNN) and Optical Character Recognition (OCR) for detecting fake Indian banknotes. In contrast to conventional methods that utilize only image classification, our system processes both visual attributes and extracted text content—identifying phrases such as “Children Bank of India” or “Not Legal Tender,” often printed on imitation banknotes. A light real-time GUI supports users in uploading currency images and obtaining immediate classification results. The dual-modality method provides improved detection accuracy, particularly against very convincing fakes. The model proves to be very accurate and scalable in design for potential future extensions to mobile devices and multi-currency detection.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Raiyan Abbas
AU  - Abhilash Kumar
AU  - C. J. Jinesh
AU  - Sridevi Sridhar
PY  - 2025
DA  - 2025/10/31
TI  - Fake Currency Detection Using Convolutional Neural Network and Textual Feature Analysis
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 875
EP  - 887
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_71
DO  - 10.2991/978-94-6463-866-0_71
ID  - Abbas2025
ER  -