Paper by Erik D. Demaine

Reference:

Jana Dambrogio, Amanda Ghassaei, Daniel Starza Smith, Holly Jackson, Martin L. Demaine, Graham Davis, David Mills, Rebekah Ahrendt, Nadine Akkerman, David van der Linden, and Erik D. Demaine, “Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography”, Nature Communications, volume 12, March 2021, Article 1184.

BibTeX

@Article{LockedLetters_NatureComm2021,
  AUTHOR        = {Jana Dambrogio and Amanda Ghassaei and Daniel Starza Smith and Holly Jackson and Martin L. Demaine and Graham Davis and David Mills and Rebekah Ahrendt and Nadine Akkerman and David van der Linden and Erik D. Demaine},
  TITLE         = {Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography},
  JOURNAL       = {Nature Communications},
  VOLUME        = 12,
  PAGES         = {Article 1184},
  MONTH         = {March},
  YEAR          = 2021,

  withstudent   = 1,
  doi           = {https://doi.org/10.1038/s41467-021-21326-w},
  comments      = {This paper is available from <A HREF="https://doi.org/10.1038/s41467-021-21326-w">Nature</A>.}
}

Abstract:

Computational flattening algorithms have been successfully applied to X-ray microtomography scans of damaged historical documents, but have so far been limited to scrolls, books, and documents with one or two folds. The challenge tackled here is to reconstruct the intricate folds, tucks, and slits of unopened letters secured shut with “letterlocking,” a practice—systematized in this paper—which underpinned global communications security for centuries before modern envelopes. We present a fully automatic computational approach for reconstructing and virtually unfolding volumetric scans of a locked letter with complex internal folding, producing legible images of the letter's contents and crease pattern while preserving letterlocking evidence. We demonstrate our method on four letterpackets from Renaissance Europe, reading the contents of one unopened letter for the first time. Using the results of virtual unfolding, we situate our findings within a novel letterlocking categorization chart based on our study of 250,000 historical letters.

Comments:

This paper is available from Nature.

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