Dynamic speckle analysis using multivariate techniques

Abstract

In this work we use principal components analysis to characterize dynamic speckle patterns. This analysis quantitatively identifies different dynamics that could be associated to physical phenomena occurring in the sample. We also found the contribution explained by each principal component, or by a group of them. The method analyzes the paint drying process over a hidden topography. It can be used for fast screening and identification of different dynamics in biological or industrial samples by means of dynamic speckle interferometry.