On how thick diffusers can contribute to the design of optical security systems

Abstract

Optical diffusers have been widely investigated from both theoretical and practical points of view.1 In particular, a large number of papers focus on numerical models related to the behavior of light interacting with such devices (see, for instance,2, 3). Despite diffusers have been investigated from multiples points of view, polarization is not a particularly interesting property in the present analysis.4 The objective of this communication is to evaluate to what extent a thick diffuser modifies and reinforces the uniqueness of the optical signature of the sample. In order to achieve this objective, we develop a ray-tracing calculation in order to determine polarization changes; data from a real diffuser surface is used. Then, experimental results validate the proposed model. Recent developments in optical authentication and validation demonstrate the ability of the properties of light to distinguish among counterfeit and true samples.5 Sometimes, metallic nanoparticles or thin films technology is used during the fabrication process in order to provide a strong polarimetric signature. In particular, the combined examination of the state of polarization of light after interacting with the sample and the statistical analysis of the speckle patterns provide enough information to train machine learning methods. In this way, these techniques would be able to predict whether the sample is true or fake.6-8 On the other hand, phase-encoding masks using cello-type diffusers provide an extra security layer. After propagation, phase encoded information becomes a Poisson-like noise distribution and thus, any attempt to access to the original signal is very difficult. In a recent paper we studied the capacity of three-dimensional phase coders using thick diffusers to enrich the amount of information for training machine learning algorithms.9 The paper is organized as follows. In section 2, we describe the numerical approach used and present several experimental results that validate the model. Finally, our conclusions are presented in section 3