Counterfeit Buster: Indian Currency Detection Using Generative Adversarial Networks
Hrutali Dhawade · International Journal for Research in Applied Science and Engineering Technology · 2025
Counterfeit currency undermines financial trust and economic stability, particularly in cash- dependent regions. As counterfeiters adopt increasingly sophisticated techniques, forged notes can evade visual inspection, rendering traditional detection methods unreliable. Furthermore, existing verification techniques are typically hardware-dependent, expensive, or too complex for general users, making them impractical and inaccessible in real-world applications. To overcome these limitations, we introduce Counterfeit Buster, an Android application that leverages Generative Adversarial Networks (GANs) for real-time detection of counterfeit Indian currency. GANs operate by training two neural networks—a generator that produces synthetic data and a discriminator that learns to distinguish it from real data—thereby enhancing detection accuracy through continuous learning. The app allows users to scan currency using their smartphone camera and receive instant results, offering a portable, affordable, and user-friendly solution. Additional features such as denomination recognition, real-time currency conversion, and voice feedback further improve accessibility and usability, empowering users to effectively combat currency fraud.