Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography

Here, the authors present a fully automatic computational approach for reconstructing and virtually unfolding volumetric scans of locked letters with complex internal folding, producing legible images of the letter’s contents and crease pattern while preserving letterlocking evidence.

Bibliographic Details
Main Authors:	Jana Dambrogio, Amanda Ghassaei, Daniel Starza Smith, Holly Jackson, Martin L. Demaine, Graham Davis, David Mills, Rebekah Ahrendt, Nadine Akkerman, David van der Linden, Erik D. Demaine
Format:	Article
Language:	English
Published:	Nature Publishing Group 2021-03-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-021-21326-w

id	doaj-0ce33d5eba684710baf3433246744129
record_format	Article
spelling	doaj-0ce33d5eba684710baf34332467441292021-03-11T11:32:57ZengNature Publishing GroupNature Communications2041-17232021-03-0112111010.1038/s41467-021-21326-wUnlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomographyJana Dambrogio0Amanda Ghassaei1Daniel Starza Smith2Holly Jackson3Martin L. Demaine4Graham Davis5David Mills6Rebekah Ahrendt7Nadine Akkerman8David van der Linden9Erik D. Demaine10Wunsch Conservation Laboratory, Massachusetts Institute of Technology (MIT) LibrariesAdobe ResearchKing’s College London, Department of English, Virginia Woolf BuildingDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyQueen Mary University of London, Institute of DentistryQueen Mary University of London, Institute of DentistryUtrecht University, Department of Media and Culture StudiesLeiden University, Leiden University Centre for the Arts in Society (LUCAS), Faculty of Humanities/English LiteratureRadboud University, Faculty of Arts, Department of History, Art History and ClassicsComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyHere, the authors present a fully automatic computational approach for reconstructing and virtually unfolding volumetric scans of locked letters with complex internal folding, producing legible images of the letter’s contents and crease pattern while preserving letterlocking evidence.https://doi.org/10.1038/s41467-021-21326-w
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Jana Dambrogio Amanda Ghassaei Daniel Starza Smith Holly Jackson Martin L. Demaine Graham Davis David Mills Rebekah Ahrendt Nadine Akkerman David van der Linden Erik D. Demaine
spellingShingle	Jana Dambrogio Amanda Ghassaei Daniel Starza Smith Holly Jackson Martin L. Demaine Graham Davis David Mills Rebekah Ahrendt Nadine Akkerman David van der Linden Erik D. Demaine Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography Nature Communications
author_facet	Jana Dambrogio Amanda Ghassaei Daniel Starza Smith Holly Jackson Martin L. Demaine Graham Davis David Mills Rebekah Ahrendt Nadine Akkerman David van der Linden Erik D. Demaine
author_sort	Jana Dambrogio
title	Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography
title_short	Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography
title_full	Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography
title_fullStr	Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography
title_full_unstemmed	Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography
title_sort	unlocking history through automated virtual unfolding of sealed documents imaged by x-ray microtomography
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2021-03-01
description	Here, the authors present a fully automatic computational approach for reconstructing and virtually unfolding volumetric scans of locked letters with complex internal folding, producing legible images of the letter’s contents and crease pattern while preserving letterlocking evidence.
url	https://doi.org/10.1038/s41467-021-21326-w
work_keys_str_mv	AT janadambrogio unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT amandaghassaei unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT danielstarzasmith unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT hollyjackson unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT martinldemaine unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT grahamdavis unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT davidmills unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT rebekahahrendt unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT nadineakkerman unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT davidvanderlinden unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography AT erikddemaine unlockinghistorythroughautomatedvirtualunfoldingofsealeddocumentsimagedbyxraymicrotomography
_version_	1724225351842791424

Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography

Similar Items