Poincare sphere noise filtering for singularities in dynamic speckle activity: Application to paint drying time measurement

Abstract

We present an approach based on optical vortex density to characterize a dynamic process. The proposal is tested in real experiments involving the drying of paint as case study. In this case, speckle patterns are generated by coherent light scattered from the sample. The dynamic behavior of the speckle pattern during the paint drying is evaluated by using Time History of Speckle Pattern (THSP). The THSP's pseudo-phase representation is calculated via a two-dimensional Laguerre Gauss transform algorithm. The singular points in the pseudo-phase are then identified, then the number of phase singularities are evaluated over all the pseudo-phase representations of the THSP sequence. A comparison between the number of the phase singularities in THSP sequences and the gravimetric curve shows that the results are in good agreement for the active period. However, for very low activity periods noise vortices are obtained. The noise vortices are originated in the camera recoding and digitalization process. We propose the use of Stokes Parameters to configure a Vortex-Filter in order to eliminate noise vortices in each paint-drying measurement, this filter is represented using Poincare Sphere for visualization purposes. In all cases, the drying evolution curve obtained by using the optical vortex density and the Poincare Sphere filter present a good agreement with gravimetric curve, indicating that the proposed method is a valid measuring alternative.