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Proceedings Paper

A pigment analysis tool for hyperspectral images of cultural heritage artifacts
Author(s): Di Bai; David W. Messinger; David Howell
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Paper Abstract

The Gough Map, in the collection at the Bodleian Library, Oxford University, is one of the earliest surviving maps of Britain. Previous research deemed that it was likely created over the 15th century and afterwards it was extensively revised more than once. In 2015, the Gough Map was imaged using a hyperspectral imaging system at the Bodleian Library. The collection of the hyperspectral image (HSI) data was aimed at faded text enhancement for reading and pigment analysis for the material diversity of its composition and potentially the timeline of its creation. In this research, we introduce several methods to analyze the green pigments in the Gough Map, especially the number and spatial distribution of distinct green pigments. One approach, called the Gram Matrix, has been used to estimate the material diversity in a scene (i.e., endmember selection and dimensionality estimation). Here, we use the Gram Matrix technique to study the within-material differences of pigments in the Gough map with common visual color. We develop a pigment analysis tool that extracts visually common pixels, green pigments in this case, from the Gough Map and estimates its material diversity. It reveals that the Gough Map consists of at least six kinds of dominant green pigments. Both historical geographers and cartographic historians will benefit from this work to analyze the pigment diversity using HSI of cultural heritage artifacts.

Paper Details

Date Published: 5 May 2017
PDF: 15 pages
Proc. SPIE 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII, 101981A (5 May 2017); doi: 10.1117/12.2261852
Show Author Affiliations
Di Bai, Rochester Institute of Technology (United States)
David W. Messinger, Rochester Institute of Technology (United States)
David Howell, Univ. of Oxford (United Kingdom)

Published in SPIE Proceedings Vol. 10198:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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