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dc.contributor.authorDambrogio, Jana L.
dc.contributor.authorGhassaei, Amanda
dc.contributor.authorStarza Smith, Daniel
dc.contributor.authorJackson, Holly
dc.contributor.authorDemaine, Martin L.
dc.contributor.authorDavis, Graham
dc.contributor.authorAhrendt, Rebekah
dc.contributor.authorAkkerman, Nadine
dc.contributor.authorvan der Linden, David
dc.contributor.authorDemaine, Erik D.
dc.date.accessioned2021-03-02T15:26:01Z
dc.date.available2021-03-02T15:26:01Z
dc.date.issued2021-03
dc.date.submitted2020-03
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/1721.1/130044
dc.description.abstractComputational flattening algorithms have been successfully applied to X-ray microtomography scans of damaged historical documents, but have so far been limited to scrolls, books, and documents with one or two folds.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.en_US
dc.publisherSpringeren_US
dc.relation.isversionofhttps://doi.org/10.1038/s41467-021-21326-wen_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleUnlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomographyen_US
dc.typeArticleen_US
dc.identifier.citationDambrogio, Jana et al. "Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography." Nature Communications 12 (March 2021): 1184. © 2021 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Librariesen_US
dc.relation.journalNature Communicationsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2021-03-02T13:45:59Z
mit.journal.volume12en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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