Comparative Analysis of Structural Similarity Index Measure (SSIM) and Oriented Fast and Rotated Brief (ORB) Algorithm for detecting fake currency
Pushpa Ravikumar, Jisha John, E K Bhoomika, R Varshini, K Kavana, B R Sai Pranam · 2025
The Fake Note Detection Project aims to evaluate and improve upon existing methods used to identify counterfeit currency. Current techniques for fake note detection include ultraviolet (UV) light analysis, magnetic ink detection, watermark verification, and microprint assessment, each with varying levels of accuracy and reliability. While these methods are widely used, they often require specialized equipment and can be time-consuming. This project reviews these existing techniques and proposes an integrated approach that combines traditional methods with modern advancements like machine learning and image processing. By utilizing regions of interest, edge detection algorithms, and feature extraction methods, we aim to improve the accuracy and efficiency of fake note detection systems. This work not only highlights the strengths and limitations of current techniques but also explores how newer technologies can enhance the detection process, ensuring a more secure and reliable system for identifying counterfeit currency.