
Proceedings Paper
Standardized system for multispectral imaging of palimpsestsFormat | Member Price | Non-Member Price |
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Paper Abstract
The Archimedes Palimpsest imaging team has developed a spectral imaging system and associated processing
techniques for general use with palimpsests and other artifacts. It includes an illumination system of light-emitting
diodes (LEDs) in 13 narrow bands from the near ultraviolet through the near infrared (▵λ≤ 40nm), blue and infrared
LEDs at raking angles, high-resolution monochrome and color sensors, a variety of image collection techniques
(including spectral imaging of emitted fluorescence), standard metadata records, and image processing algorithms,
including pseudocolor color renderings and principal component analysis (PCA). This paper addresses the development
and optimization of these techniques for the study of parchment palimpsests and the adaptation of these techniques to
allow flexibility for new technologies and processing capabilities. The system has proven useful for extracting text from
several palimpsests, including all original manuscripts in the Archimedes Palimpsest, the undertext in a privately owned
9th-century Syriac palimpsest, and in a survey of selected palimpsested leaves at St. Catherine's Monastery in Egypt. In
addition, the system is being used at the U.S. Library of Congress for spectral imaging of historical manuscripts and
other documents.
Paper Details
Date Published: 16 February 2010
PDF: 11 pages
Proc. SPIE 7531, Computer Vision and Image Analysis of Art, 75310D (16 February 2010); doi: 10.1117/12.839116
Published in SPIE Proceedings Vol. 7531:
Computer Vision and Image Analysis of Art
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)
PDF: 11 pages
Proc. SPIE 7531, Computer Vision and Image Analysis of Art, 75310D (16 February 2010); doi: 10.1117/12.839116
Show Author Affiliations
Roger L. Easton Jr., Rochester Institute of Technology (United States)
Keith T. Knox, Air Force Research Lab. (United States)
William A. Christens-Barry, Equipoise Imaging, LLC (United States)
Kenneth Boydston, Megavision Inc. (United States)
Keith T. Knox, Air Force Research Lab. (United States)
William A. Christens-Barry, Equipoise Imaging, LLC (United States)
Kenneth Boydston, Megavision Inc. (United States)
Michael B. Toth, R. B. Toth Associates (United States)
Doug Emery, Emery IT (United States)
William Noel, Walters Art Museum (United States)
Doug Emery, Emery IT (United States)
William Noel, Walters Art Museum (United States)
Published in SPIE Proceedings Vol. 7531:
Computer Vision and Image Analysis of Art
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)
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