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[Multispectral imaging of degraded parchment]

Multispectral imaging of degraded parchment

Lindsay MacDonald1,  Alejandro Giacometti1,  Alberto Campagnolo2,  Stuart Robson1,  Tim Weyrich1,  Melissa Terras1,  Adam Gibson1

1 University College London
2 University of the Arts London

Abstract

Multispectral imaging was employed to collect data on the degradation of an 18th century parchment by a series of physical and chemical treatments. Each sample was photographed before and after treatment by a monochrome digital camera with 21 narrow-band filters, with the objective of assessing algorithms for recovery of text from the images. A template-matching technique was used to detect the circular holes in each sample and a four-point projective transform to register the 21 images. Colour accuracy was verified by comparison of reconstructed spectra with measurements by spectrophotometer.

Citation Style:    Publication

Multispectral imaging of degraded parchment.
Lindsay MacDonald, Alejandro Giacometti, Alberto Campagnolo, Stuart Robson, Tim Weyrich, Melissa Terras, Adam Gibson.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7786, pp. 143–157, March 2013.Lindsay MacDonald, Alejandro Giacometti, Alberto Campagnolo, Stuart Robson, Tim Weyrich, Melissa Terras, and Adam Gibson. Multispectral imaging of degraded parchment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7786:143–157, March 2013.MacDonald, L., Giacometti, A., Campagnolo, A., Robson, S., Weyrich, T., Terras, M., and Gibson, A. 2013. Multispectral imaging of degraded parchment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7786 (Mar.), 143–157.L. MacDonald, A. Giacometti, A. Campagnolo, S. Robson, T. Weyrich, M. Terras, and A. Gibson, “Multispectral imaging of degraded parchment,”Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7786, pp. 143–157, Mar. 2013.
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