Thematic Einstein Semester on
Geometric and Topological Structure of Materials
Summer Semester 2021
Speaker
Claudia Redenbach (TU Kaiserslautern)
Title
Using stochastic models for segmentation and characterization of spatial microstructures
Abstract
The performance of engineering materials such as foams, fibre composites or concrete is heavily influenced by the microstructure geometry. Quantitative analysis of 3D images, provided for instance by micro computed tomography (μCT), allows for a characterization of material samples. In this talk, we will illustrate how models from stochastic geometry may support the segmentation of image data and the statistical analysis of the microstructures. One example deals with the estimation of the fibre length distribution from μCT images of glass fibre reinforced composites. Examples of segmentation tasks are the reconstruction of the solid component of a porous medium from focused ion beam scanning electron microscopy (FIB-SEM) image data and the segmentation of cracks in μCT images of concrete. In both cases, the tasks are solved by using convolutional neural networks trained on synthetic images of realizations of stochastic geometry models.
Contact
tes-summer2021@math.tu-berlin.de