AUTOMATIC AND INTERACTIVE CORRELATION PARTITIONING COMPARED - APPLICATION TO TIN TI/SIO2/

A new method has been developed for the partitioning of sets of images with the objective of automatically identifying the number and locati ons of different regions in a material, The method is called automatic correlation partitioning and it involves the identification of cluste rs in the n-dimensional intensity histogram of a set of n images that are spatially registered, The method uses the peaks located in the sim ple intensity histograms of each image in the set to produce a list of all possible clusters in the entire data set, This list is then searc hed in order to find the actual clusters, The method is tested using d ata from a multi-imaging Auger electron microscope, which yields sets of Auger images characteristic of the spatial distributions of selecte d kinds of atoms in the surface of a solid, The first tests involve th e use of a model sample consisting of a W overlay pattern on a Si subs trate, The second tests are done on a TiN/Ti/SiO2 planar layer structu re that has been ion beam bevelled to reveal a cross-section of the co mposition depth profile, The first set contains two images and the sec ond set contains five images, The results of the new automatic method are compared with those obtained by the analyst working interactively with the data set to identify the clusters subjectively, Cluster analy sis of the second sample reveals details of the interfacial layer chem istry not revealed by the interactive method and is consistent with pu blished XPS depth profiling experiments reporting a titanium silicide layer at the Ti/SiO2 interface.