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

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.