Abstract
In surface science, Scanning Auger Microscopy (SAM) is an important method for investigating the chemical composition of surfaces and obtaining information about the spatial distribution of chemical elements. Images obtained by SAM give a qualitative impression of the concentration of the selected elements on the surface. For the systematic characterization of inhomogeneous materials the evaluation of multispectral SAM-images can be facilitated by image processing techniques. Two methods, classification and segmentation, are applied to SAM images and the results are compared. Scatter diagrams have been used to classify the number and coverage of different surface phases. In SAM-literature (e.g. [1]) it is demonstrated that classification is a valuable and easy to use tool to interpret the content of multispectral images. Segmentation decomposes the images into homogeneous connected regions of similar surface composition, based on the information contained in the elemental maps. Segmentation makes it possible to extract statistical and topological features of single objects, whereas scatter diagram analysis gives information only about different surface phases.
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