Presentation
22 July 2019 Machine learning analysis of illuminated Southeast Asian manuscripts using complementary noninvasive imaging techniques (Conference Presentation)
Author Affiliations +
Abstract
The complementary use of X-ray fluorescence (XRF) mapping, spectral imaging, and Raman mapping, allows for the analysis and identification of important artistic materials used in the production and illustration of illuminated manuscripts. This project uses combined non-invasive imaging techniques to analyse 17th – 19th century manuscripts from the British Library’s Southeast Asia Collections so that more can be understood about the adoption and evolution of artistic materials and techniques used in Maritime Southeast Asia. Using multiple different imaging techniques has shown to provide positive results, however, a consequence of this is the collection of large amounts of data, necessitating the automatic and unsupervised analytical techniques used in machine learning. Data collected in-situ at the British Library using macro-XRF mapping, macro-Raman mapping, and Spectral Imaging, will be analysed using a range of machine learning techniques to cluster pixel information representing materials used in southeast Asian manuscripts.
Conference Presentation
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Luke Butler, Sotiria Kogou, Yu Li, Chi Shing Cheung, Haida Liang, Annabel T. Gallop, Paul Garside, and Christina Duffy "Machine learning analysis of illuminated Southeast Asian manuscripts using complementary noninvasive imaging techniques (Conference Presentation)", Proc. SPIE 11058, Optics for Arts, Architecture, and Archaeology VII, 110581M (22 July 2019); https://doi.org/10.1117/12.2527576
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KEYWORDS
Machine learning

Associative arrays

Imaging spectroscopy

Raman spectroscopy

X-ray fluorescence spectroscopy

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