Print Email Facebook Twitter Characterization of Hidden Paint Layer Topography Using a Stereographic XRF Approach Title Characterization of Hidden Paint Layer Topography Using a Stereographic XRF Approach Author Allred, Jennie (TU Delft Mechanical, Maritime and Materials Engineering) Contributor Dik, J. (mentor) Degree granting institution Delft University of Technology Programme Materials Science and Engineering Date 2017-12-21 Abstract Scientific investigation of paintings has been facilitated by the development of advanced non-de\-struc\-tive imaging methods. Characterization of painting stratigraphy traditionally requires extraction of small paint samples, thereby limiting its use to a few locations on a painting due to its destructive nature. Alternatively, non-destructive analysis of paint layer stratigraphy and structure across an entire painting often requires highly specialized and costly equipment, and/or the transport of priceless artworks. In addition, most methods are also typically limited to a localized point analysis. This document proposes an alternative method for the substructure examination of paintings using a mobile macro-XRF spectrometer and a stereographic approach with reduced step sizes. This is coupled with a novel data analysis method which will enable a global study of the topographical features of hidden paint layers. As a prototype to test the feasibility of the method, we utilized a two-layer test sample consisting of pastose bone black pigment on pastose lead white, with an aluminum substrate. High resolution 3D optical microscopy was utilized to establish a ground truth for the thicknesses of both paint layers. Through successful registration of MA-XRF scans obtained with varying detector geometries into a single hyrbid image, we were able to find a strong correlation between the quanitative height data obtained with optical microscopy and our hybrid XRF image. Our findings indicate that utilizing this approach for visualizing hidden paint layer topographies proves to be very promising. Coupled with novel data fusion algorithms and visualization techniques, additional insight about painterly technique can thus be gained by utilizing existing MA-XRF scanners to scan a painting in multiple orientations. Subject XRFhidden paint layerspaintings To reference this document use: http://resolver.tudelft.nl/uuid:e075771f-a53f-4790-8bdc-673381e7664f Part of collection Student theses Document type master thesis Rights © 2017 Jennie Allred Files PDF thesis.pdf 8.53 MB Close viewer /islandora/object/uuid:e075771f-a53f-4790-8bdc-673381e7664f/datastream/OBJ/view