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Medicine Tablet Authentication Using 'Fingerprints' of Ink-Jet Printed Characters

机译:使用喷墨打印字符的“指纹”对药品平板电脑进行身份验证

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摘要

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.
机译:假药一直是严重的问题,对全世界人民的健康造成损害。提出了多种基于标签的防伪方法。但是,它们存在三个主要问题:(1)标记仅适用于包装,不适用于平板电脑; (2)最终用户(即患者)无法检查标签; (3)标记会增加制造商的成本。本文介绍了一种新的方法,我们建议通过匹配打印字符的图像来原样验证单个药丸。相同药物的各个片剂上的印刷字符在人眼看来似乎相同,但每个字符都具有微小的独特差异。本文的贡献是:(a)揭示由实际药物使用的机器打印的字符的唯一性,以及(b)提出一种实用的系统,通过图像匹配来识别单个药片。我们的系统对任何想要认证手头药片的患者都非常有用:它仅需要使用智能手机相机拍摄的照片。我们的系统对药品制造商也很有用,因为可以使用现有制造过程来构建数据库,而不会产生额外费用。我们的图像匹配算法可以识别图像的非常详细的特征,即使对于大型数据库也可以准确,快速地进行。在进行的实验中,使用与实际药品制造机相同的光学装置捕获了1,000个样品片剂。获得的结果表明,个人平板电脑身份验证的准确性达到了100%。

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