Industrial Application of a High-Speed and High-Accuracy Authenticity Judgment System Using Unclonable Printed Codes

Abstract

In today's online commerce, the easy distribution of counterfeit products, such as food, brand-name products, and pharmaceuticals, has become a serious social problem in terms of economy and safety. To address this problem, we propose a system for determining the authenticity of 2D codes printed by inkjet printers; it leverages the micro-scale nature of the ink sequences in the codes, which are difficult to duplicate. The proposed system combines locally likely arrangement hashing, which performs a fast search for similar images, and Accelerated-KAZE, which performs high-precision feature matching, to determine the authenticity of images taken with a smartphone. The results of our study demonstrated the high effectiveness of our system in terms of accuracy, discriminability, and speed by validating it on a large dataset of 15,000 images. The system was also validated for industrial applications by verifying its scalability for low-cost industrial media printing and monochrome printing as well as its robustness to rotation, scale change, and smudging.