Entropy-based Inhomogeneity Detection in Fiber Materials

We study a change-point problem for random fields based on a univariate detection of outliers via the 3 σ -rule in order to recognize inhomogeneities in glass fiber reinforced polymers (GFRP). In particular, we focus on GFRP modeled by stochastic fiber processes with high fiber intensity and search for abrupt changes in the direction of the fibers. As a measure of change, the entropy of the directional distribution is locally estimated within a window that scans the region to be analyzed.