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Limiting Factors in Smartphone-Based Cross-Sensor Microstructure Material Classification

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Digital Forensics and Watermarking (IWDW 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14511))

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Abstract

Intrinsic, non-invasive product authentication is the preferred way of detecting counterfeit products as it does not generate additional costs during the production process. Previous works achieved promising results for smartphone-based product authentication. However, while promising, the methods fail when enrollment and authentication are performed on different devices (cross-device). This work investigates the underlying reasons for the limitations in the practical application of cross-device intrinsic surface structure-based product authentication. In particular by utilising micro-texture classification approaches applied on images of zircon oxide blocks (dental implants) captured using a commodity smartphone device. The main result is that the device-specific artefacts (image sensor as well as image processing-specific ones) are so strong that they obfuscate the material microstructure. To be more precise, the device’s intrinsic signal makes device identification easier to perform than the material authentication.

This research was partially funded by the Salzburg State Government within the Science and Innovation Strategy Salzburg 2025 (WISS 2025) under the project AIIV-Salzburg (Artificial Intelligence in Industrial Vision), project no 20102-F2100737-FPR.

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Authors and Affiliations

  1. Department of Artificial Intelligence and Human Interfaces, University of Salzburg, Salzburg, Austria

    Johannes Schuiki, Christof Kauba, Heinz Hofbauer & Andreas Uhl

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  1. Johannes Schuiki
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  2. Christof Kauba
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  3. Heinz Hofbauer
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  4. Andreas Uhl
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Correspondence to Johannes Schuiki .

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Editors and Affiliations

  1. School of Cyber Security, Qilu University of Technology, Jinan, China

    Bin Ma

  2. Qilu University of Technology, Jinan, China

    Jian Li

  3. Qilu University of Technology, Jinan, China

    Qi Li

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Schuiki, J., Kauba, C., Hofbauer, H., Uhl, A. (2024). Limiting Factors in Smartphone-Based Cross-Sensor Microstructure Material Classification. In: Ma, B., Li, J., Li, Q. (eds) Digital Forensics and Watermarking. IWDW 2023. Lecture Notes in Computer Science, vol 14511. Springer, Singapore. https://doi.org/10.1007/978-981-97-2585-4_3

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  • DOI: https://doi.org/10.1007/978-981-97-2585-4_3

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  • Online ISBN: 978-981-97-2585-4

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