In this study, µ-XRF was applied as a novel surface technique for quick acquisition of elemental X-ray maps of rocks, image analysis of which provides quantitative information on texture and rock-forming minerals. Bench-top µ-XRF is cost-effective, fast, and non-destructive, can be applied to both large (up to a few tens of cm) and fragile samples, and yields major and trace element analysis with good sensitivity. Here, X-ray mapping was performed with a resolution of 103.5 µm and spot size of 30 µm over sample areas of about 5×4 cm of Euganean trachyte, a volcanic porphyritic rock from the Euganean Hills (NE Italy) traditionally used in cultural heritage. The relative abundance of phenocrysts and groundmass, as well as the size and shape of the various mineral phases, were obtained from image analysis of the elemental maps. The quantified petrographic features allowed identification of various extraction sites, revealing an objective method for archaeometric provenance studies exploiting µ-XRF imaging.

A mean-shift clustering (MSC) algorithm is introduced as a valuable alternative to perform materials phase classification from multispectral images. As opposed to other multivariate statistical techniques, such as factor analysis or principal component analysis (PCA), clustering techniques directly assign a class label to each pixel, so that their outputs are phase segmented images, i.e., there is no need for an additional segmentation algorithm. On the other hand, as compared to other clustering procedures and classification methods, such as segmentation by thresholding of multiple spectral components, MSC has the advantages of not requiring previous knowledge of the number of data clusters and not assuming any shape for these clusters, i.e., neither the number nor the composition of the phases must be previously known. This makes MSC a particularly useful tool for exploratory research, assisting phase identification of unknown samples. Visualization and interpretation of the results are also simplified, since the information content of the output image does not depend on the particular choice of the content of the color channels. We applied MSC to the analysis of two sets of X-ray maps acquired in scanning electron microscopes equipped with energy-dispersive detection systems. Our results indicate that MSC is capable of detecting additional phases, not clearly identified through PCA or multiple thresholding, with a very low empirical reject rate.

Multielemental X-ray maps collected by a remote scanning system of the electron beam are processed by a dedicated software program performing accurate modal determination of geological samples. The classification of different mineral phases is based on elemental concentrations. The software program Petromod loads the maps into a database and computes a matrix consisting of numerical values proportional to the elemental concentrations. After an initial calibration, the program can perform the chemical composition calculated on the basis of a fixed number of oxygens for a selected area. In this way, it is possible to identify all the mineral phases occurring in the sample. Up to three elements can be selected to calculate the modal percentage of the identified mineral. An automated routine scans the whole set of maps and assigns each pixel that satisfies the imposed requirements to the selected phase. Repeating this procedure for every mineral phase occurring in the mapped area, a modal distribution of the rock-forming minerals can be performed. The final output consists of a digitized image, which can be further analyzed by common image analysis software, and a table containing the calculated modal percentages. The method is here applied to a volcanic and a metamorphic rock sample.