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Proceedings Paper

Validation of optical codes based on 3D nanostructures
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Paper Abstract

Image information encoding using random phase masks produce speckle-like noise distributions when the sample is propagated in the Fresnel domain. As a result, information cannot be accessed by simple visual inspection. Phase masks can be easily implemented in practice by attaching cello-tape to the plain-text message. Conventional 2D-phase masks can be generalized to 3D by combining glass and diffusers resulting in a more complex, physical unclonable function. In this communication, we model the behavior of a 3D phase mask using a simple approach: light is propagated trough glass using the angular spectrum of plane waves whereas the diffusor is described as a random phase mask and a blurring effect on the amplitude of the propagated wave. Using different designs for the 3D phase mask and multiple samples, we demonstrate that classification is possible using the k-nearest neighbors and random forests machine learning algorithms.

Paper Details

Date Published: 10 May 2017
PDF: 6 pages
Proc. SPIE 10219, Three-Dimensional Imaging, Visualization, and Display 2017, 102190M (10 May 2017); doi: 10.1117/12.2262417
Show Author Affiliations
Artur Carnicer, Univ. de Barcelona (Spain)
Bahram Javidi, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 10219:
Three-Dimensional Imaging, Visualization, and Display 2017
Bahram Javidi; Jung-Young Son; Osamu Matoba, Editor(s)

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