Abstract
Most approaches for product counterfeit detection are based on identification using some unique marks or properties implemented into each single product or its package. In this paper we investigate a classification approach involving existing packaging only in order to avoid higher production costs involved with marking each individual product. To detect counterfeit packages, images of the package’s interior showing the plain structure of the paperboard are captured. Using various texture features and SVM classification we are able to distinguish drug packages coming from different manufacturers and also forged packages with high accuracy while a distinction between single packages of the same manufacturer is not possible.
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Acknowledgments
This work is supported by the Munich based software venture eMundo which receives funding from the Central Innovation Program for SMEs by Germany’s Federal Ministry of Economics and Technology (project “FakeFinder” no. ZIM-EP150145).
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Kauba, C., Debiasi, L., Schraml, R., Uhl, A. (2016). Towards Drug Counterfeit Detection Using Package Paperboard Classification. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9917. Springer, Cham. https://doi.org/10.1007/978-3-319-48896-7_14
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DOI: https://doi.org/10.1007/978-3-319-48896-7_14
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