AI Surveillance against Counterfeit Notes - Sandeep Ghorpade; Rihan Kadekar; Harshvardhan Mahajan; Shailesh Sahane; Prof. A. V. Dhamal (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
The project “AI surveillance against counterfeit notes” aims to develop an intelligent system capable of detecting and identifying currency denominations from both static images and live webcam input. The system utilizes machine learning and computer vision techniques to recog nize different currency notes efficiently and accurately. A React-based frontend enables users to upload images or use a live webcam for real-time detection. The backend (optional) or in browser TensorFlow.js model performs inference, providing denomination labels, confidence scores, and bounding boxes on the detected notes. This application is particularly useful for assisting visually impaired individuals, automated teller machines, and cash-sorting systems, offering a fast, reliable, and user-friendly interface. The model is trained on a dataset of cur rency images with varied lighting, orientation, and background conditions to enhance accuracy and robustness. With a prototype accuracy target above 90, this project demonstrates the po tential of lightweight machine learning models in real-time visual currency recognition.