Development of a Mobile App to Detect Counterfeit Currency using Machine Learning
Rakesh K. Kadu, Praneet Gupta, Pranay Jain, Saurabh Nakade · 2023
Counterfeit poses a serious threat to financial institutions and the global economy. This work introduces machine learning techniques that use image processing, pattern recognition, and classification algorithms to accurately identify false positives. These studies are based on analysis of real banknotes, their security features and counterfeiting techniques. Images of real and fake invoices are carefully recorded to create robust data for training and testing learning models such as neural networks (CNN). Image processing techniques such as edge detection and feature extraction improve the model's detection capabilities. The development model, evaluated in terms of efficiency, is integrated into a user-friendly interface and accepts cash register images as input. This solution aims to contribute to continuous efforts to combat fraud, providing a clear and effective way to protect financial institutions and increase business security.