2022 Volume 10 Issue 1 Pages 82-88
The distribution of easily imitated counterfeit products, such as food packaging, brand tags, and pharmaceutical labels, has become a serious economic and safety concern. To address this issue, we propose a system for authenticity judgment of genuine and counterfeit products with high speed and accuracy, focusing on the physically unclonable function of an inkjet-printed code and a locally likely arrangement hashing (LLAH) system that performs high-speed image retrieval. In this study, we verified that the proposed system has high discriminability and stability, based on highly accurate results obtained from a dataset of up to 4,000 sheets. In addition, the effectiveness of the system was also confirmed by validating it on multiple printers and comparing it with Oriented FAST and Rotated BRIEF (ORB), a typical feature matching method, in terms of discriminability and speed.
