Eventi 2019
The material study of ancient coins is very often rendered particularly challenging by several factors: the presence of surface alteration products; the occasional or deliberate, e.g., forgery, changes in the composition of the base alloy; the misleading information deriving from historical and literature sources.
We present herewith a multi-analytical approach to the study of ancient coins.
X-ray diffraction-X-ray fluorescence (XRD-XRF) data sets obtained from surface scans of synthetic samples have been analyzed using different data clustering algorithms, to propose a methodology for automatic crystallographic and chemical classification of surfaces.
Three data clustering strategies have been evaluated, namely hierarchical, k-means, and density-based clustering; all of them have been applied to the distance matrix calculated from the single XRD and XRF data sets as well as the combined distance matrix.
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