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Automated Anticounterfeiting Inspection Methods for Rigid Films Based on Infrared and Ultraviolet Pigments and Supervised Image Segmentation and Classification

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Knowledge-Based and Intelligent Information and Engineering Systems (KES 2010)

Abstract

Anticounterfeiting of, e.g., pharmaceutical products guarrantees customers the delivery of original products. The rigid film industry is developing automated systems to detect product piracy. For this aim, an approach to an automated inspection system for rapid and reliable product verification based on infrared (ir) and ultraviolet (uv) μm-pigments in rigid films has been developed and statistically meaningful samplesets have been extracted. The industrial manufacturing process has been enhanced for optimized insertion of pigments in rigid films with regard to size, type, and density. The pigments are activated with infrared or ultraviolet light in an encapsulated laboratory system specially developed here. Filter on illumination sources and colour cameras limit the activation and the emission range. Due to optimized film manufacturing and measurement system, the evaluation for uv-pigments can be achieved by a two-stage process of state of the art supervised colour segmentation and blob analysis. The recognition results of the conceived intelligent engineering system fully meets the industrial specification requirements.

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© 2010 Springer-Verlag Berlin Heidelberg

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Kohlert, M., Kohlert, C., König, A. (2010). Automated Anticounterfeiting Inspection Methods for Rigid Films Based on Infrared and Ultraviolet Pigments and Supervised Image Segmentation and Classification. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15387-7_36

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  • DOI: https://doi.org/10.1007/978-3-642-15387-7_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15386-0

  • Online ISBN: 978-3-642-15387-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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