Pigment Analysis: Difference between revisions

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Camille Polkownik
Client: Camille Polkownik, [[Hamilton Kerr Institute]] <cp574@cam.ac.uk>


Hamilton Kerr Institute - Fitzwilliam Museum
Painting conservators at the Hamilton Kerr Institute often identify pigment substances in paint by analysing microscope images. They need a tool that enhances their expert judgment, using computer vision algorithms from the OpenCV library to automate mundane classification tasks. This interactive tool should provide a structured and flexible decision process that optimises search for the most likely substance, by allowing the conservator to quickly eliminate unlikely possibilities, and to focus on those properties that seem most ambiguous or problematic for any particular sample.
 
2017
 
Proposal for a student project
Build an Interactive and Intuitive Tool
to Assist Art Conservators in Pigment Analysis
 
The Project
 
Build an interactive tool (website or app) that would enable conservators to identify
pigments through their microscopic characteristics.
The reason why we would like to make this a student project is that this educational
tool would be in online and in free-access . It would benefit students and recent graduates
in conservation as well as older conservators who use polarised light microscopy every now and
then and need the support. It also offers the IT student a collaboration with professionals and
most of all, a multidisciplinary experience .
 
How are pigments analysed?
 
As of 2017, various methods are available to analyse pigments. To cite a few, there is:
x-ray fluorescence (XRF), Macro X-ray fluorescence (MA-XRF), SEM-EDX (Scanning Electron
Microscopy with Energy Dispersive X-Ray analysis), FTIR (Fourier transform infrared
spectroscopy). The major drawback with all these methods is the price: they are expensive to
acquire and need specific knowledge of the machine and its limitations.
Another method to analyse pigment exist: polarised light microscopy (PLM). It has the
potential of solving problems confidently and quickly , as the sample set-up and analysis can
be done under 15-20 minutes. Plus, the investment is minimal , one needs a hot plate and
glass slides for the mounting of samples and a good microscope.
 
What is currently available to support pigment analysis?
- Flowcharts (paper): very rigid . If one characteristic is missed then it is impossible to go
on.
- McCrone Atlas ( www.mccroneatlas.com ): not adapted for historical pigments.
- Pigment Compendium: dictionary, not an analytical tool . (Eastaugh, N., Walsh, V.,
Chaplin, T., and Siddall, R., 2004. The Pigment Compendium: Dictionary of Historical
Pigments , Oxford: Elsevier Butterworth-Heinemann)
 
Who would use the interactive tool?
 
The survey done in July 2017 received 226 responses, mostly from conservators
interested in the project and sharing they would like to have access to such a tool. A few even
offered to test it for us before the launch. Interviews with conservation students and emerging
and settled conservators alike showed that such a tool would be welcome and would provide
support which would itself bring more confidence.
 
How is the tool different and useful?
The tool would work as a deconstructed flowchart : the conservator can start with
whichever characteristic he/she wants. The more characteristics you enter, the few options are
presented, narrowing the search. This is more intuitive and allows more freedom as the
analysis is not always straightforward.
 
Additional information
- The content is being written up by myself, based on available information in the
Pigment Compendium and information from flowcharts.
- The website/app would be supported by the IT staff from the Fitzwilliam Museum
and would be hosted at the Hamilton Kerr Institute in Whittlesford.
- The design, amongst other things, would be up to the student and every aspect
would be discussed to produce the most accurate project.

Latest revision as of 15:29, 22 October 2017

Client: Camille Polkownik, Hamilton Kerr Institute <cp574@cam.ac.uk>

Painting conservators at the Hamilton Kerr Institute often identify pigment substances in paint by analysing microscope images. They need a tool that enhances their expert judgment, using computer vision algorithms from the OpenCV library to automate mundane classification tasks. This interactive tool should provide a structured and flexible decision process that optimises search for the most likely substance, by allowing the conservator to quickly eliminate unlikely possibilities, and to focus on those properties that seem most ambiguous or problematic for any particular sample.