Print Email Facebook Twitter Medicine tablet authentication using fingerprints of ink-jet printed characters Title Medicine tablet authentication using fingerprints of ink-jet printed characters Author Ishiyama, Rui (NEC Corporation) Takahashi, Toru (NEC Corporation) Makino, Kengo (NEC Corporation) Kudo, Yuta (NEC Corporation) Kooper, Martin (Student TU Delft) Abbink, D.A. (TU Delft Human-Robot Interaction) Date 2019 Abstract Counterfeit drugs have been a serious problem causing damage to people's health over the world. Numerous anti-counterfeiting methods based on tagging have been proposed; however, they suffer from three major issues: (1) tagging is applicable only to packages, not tablets directly; (2) end-users, i.e., patients, cannot inspect the tags; (3) tagging incurs extra costs for manufacturers. This paper describes a new method that we propose for authenticating individual medicine tablets as-is by matching images of printed characters. The printed characters on individual tablets of the same medicine seem the same to human eyes, but each is characterized by tiny unique differences. The contributions of this paper are: (a) to reveal the uniqueness of the characters printed by an actual pharmaceutical-use machine and (b) to propose a practical system to identify individual tablets using image matching. Our system is useful for any patients who want to authenticate a medicine tablet at hand: it only requires a picture with a smartphone camera. Our system is also useful for medicine manufacturers, because the database can be constructed using the existing manufacturing process without incurring additional cost. Our image matching algorithm recognizes very detailed features of the images and is accurate and fast even for a large-scale database. In conducted experiments, 1,000 sample tablets were captured using the same optical setup as an actual medicine manufacturing machine. Obtained results showed that 100% accuracy in individual tablet authentication was achieved. Subject Anti-counterfeitArtifact metricsAuthenticationFingerprintingFourier-Mellin phase correlationIdentificationImage matchingMedicine tabletPhysically unclonable function To reference this document use: http://resolver.tudelft.nl/uuid:180ee978-7120-476f-b9c7-4f8f44d5f1c5 DOI https://doi.org/10.1109/ICIT.2019.8754966 Publisher IEEE, Piscataway, NJ, USA ISBN 978-1-5386-6376-9 Source Proceedings - 2019 IEEE International Conference on Industrial Technology (ICIT 2019) Event 2019 IEEE International Conference on Industrial Technology, ICIT 2019, 2019-02-13 → 2019-02-15, Melbourne, Australia Series Proceedings of the IEEE International Conference on Industrial Technology, 2019-February Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2019 Rui Ishiyama, Toru Takahashi, Kengo Makino, Yuta Kudo, Martin Kooper, D.A. Abbink Files PDF 24986_ICIT2019_MedTabID_1 ... 0111fc.pdf 1.2 MB Close viewer /islandora/object/uuid:180ee978-7120-476f-b9c7-4f8f44d5f1c5/datastream/OBJ/view