Segmentation of elemental EDS maps by means of multiple clustering combined with phase identification

Abstract

An imaging concept is proposed for the phase identification and segmentation of elemental map images from energy dispersive spectroscopy. The procedure starts with presegmentation using common clustering algorithms, continues with automated identification of the chemical compositions, followed by their screening by professional expertise. The ultimate phases are finally clustered by applying a minimum Euclidean distance classifier. The potential, performance and limitations of the approach are presented on energy dispersive spectroscopy maps acquired by a scanning electron microscope and conducted on samples produced from cement clinker, natural rock and hydrated cement mortar. Nevertheless, the technique is suitable for arbitrary types of materials and general devices for energy dispersive spectroscopy acquisition. It is an approach for extending common energy dispersive spectroscopy analysis by means of visual examination and ratio plots towards quantitative rating.