Staff View
Methods for photographic steganography and radar object shape inference

Descriptive

TitleInfo
Title
Methods for photographic steganography and radar object shape inference
Name (type = personal)
NamePart (type = family)
Wengrowski
NamePart (type = given)
Eric
NamePart (type = date)
1991-
DisplayForm
Eric Wengrowski
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Dana
NamePart (type = given)
Kristin
DisplayForm
Kristin Dana
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Meer
NamePart (type = given)
Peter
DisplayForm
Peter Meer
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Patel
NamePart (type = given)
Vishal
DisplayForm
Vishal Patel
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Hoogs
NamePart (type = given)
Anthony
DisplayForm
Anthony Hoogs
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (encoding = w3cdtf); (qualifier = exact)
2019
DateOther (encoding = w3cdtf); (qualifier = exact); (type = degree)
2019-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2019
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract
In this work, we explore the fundamental problems associated with Photographic Steganography, the process of discretely sending information camouflaged in natural images from electronic display to camera. Broadly stated, the goals are minimizing the perceived visual impact of adding a new message to an image, while simultaneously maximizing the ability to accurately recover this message camera-side. This process is complicated by the photometric and radiometric effects of cameras, electronic displays, and their relative geometry and illumination conditions. In Chapter 2, we model these effects jointly as a Camera-Display Transfer Function (CDTF) and introduce two online radiometric calibration techniques to mitigate the effects of the CDTF. In Chapter 3, we extend photographic steganography by modeling and predicting color shifts that minimize perceptual impact and maximize accurate camera recovery. In Chapter 4, we use deep convolutional neural networks to jointly learn a steganographic embedding and recovery algorithm that requires no multi-frame synchronization, one of the most significant practical barriers to success for photographic steganography. The proposed techniques have all been implemented in real-time demos using consumer-grade displays and smartphone cameras. This body of work represents a fundamental contribution to the field of camera-display communication and photographic steganography. Chapter 5 explores how computer vision techniques can be extended to monostatic radar for shape recognition.
Subject (authority = local)
Topic
Photographic steganography
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
Subject (authority = ETD-LCSH)
Topic
Image steganography
Subject (authority = ETD-LCSH)
Topic
Machine learning
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_9857
PhysicalDescription
Form (authority = gmd)
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xii, 106 pages) : illustrations
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/t3-kxd9-y516
Genre (authority = ExL-Esploro)
ETD doctoral
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Wengrowski
GivenName
Eric
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-04-12 22:21:04
AssociatedEntity
Name
Eric Wengrowski
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
Type
Embargo
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2019-11-30
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after November 30th, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
CreatingApplication
Version
1.5
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2019-04-14T23:42:07
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2019-04-14T23:42:07
ApplicationName
pdfTeX-1.40.18
Back to the top
Version 8.5.5
Rutgers University Libraries - Copyright ©2024