Paper Currency: A systematic review of design, security features, and counterfeit detection

Abstract

Counterfeiting of currency notes remains a persistent global challenge with extensive economic consequences. This systematic review provides a comprehensive analysis of the detection techniques employed to combat counterfeit currency, involving various countries. The aim is to synthesize and evaluate the effectiveness of these methods, highlighting on the advancements made, and classifying areas of research with respect to its security features, conventional detection techniques, fuzzy logic and image processing techniques and other methods. One of the central themes emerging from this analysis is the importance of security features in currency design. Technological advancements have catalyzed the development of advanced detection tools and automated frameworks. Researchers have explored machine learning algorithms, image processing, and data-driven approaches to detect counterfeit notes efficiently. Additionally, this systematic review identifies the significance of cross-disciplinary collaboration. It emphasizes the need for cooperation between graphic designers, printers, papermakers, and central banks to create secure currency designs and implement effective detection mechanisms. Moreover, the geographical scope of this review extends to various countries where each region faces unique challenges and employs distinct methods to detect counterfeit notes, reflecting the global diversity in counterfeit threats. As the threat of counterfeit currency continues to evolve, this case by case analysis will serve as a valuable resource for banking and financial sectors, and researchers seeking to enhance counterfeit detection strategies and safeguard economies worldwide.