New Algorithms for 3-D Imaging and Analysis of Open-Celled Foams

Abstract

Open-celled foams are three-dimensional networks of polymeric cells. The mechanical properties of a foam depend on the size and geometry of its cells. Since foams have a three-dimensional polyhedral structure, the two-dimensional characterization techniques currently used provide limited accuracy. Nuclear magnetic resonance and x-ray tomography methods offeropportunities for three-dimensional imaging of these polyhedral structures. Software, which can use digital three-dimensional images to determine structural parameters such as strut length distribution, connectivity, and cell size, is being developed. The image processing approach uses conformal curvature flow (CCF)segmentation to find the surfaces of foam struts in the 3-D images. Once these surfaces have been found, volume thinning is used to find the structural skeleton of the foam. The resulting data set can then be used to determine many statistical characteristics of the foam, including strut length distributions, window size and shape distributions, and cell size information. Analysis of a reticulated polyurethane foam sample using these methods yielded a reasonable approximation of the structural skeleton of the sample.