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Methods for photographic steganography and radar object shape inference
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Wengrowski, Eric. Methods for photographic steganography and radar object shape inference. Retrieved from https://doi.org/doi:10.7282/t3-kxd9-y516

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TitleMethods for photographic steganography and radar object shape inference
NameWengrowski, Eric (author); Dana, Kristin (chair); Meer, Peter (internal member); Patel, Vishal (internal member); Hoogs, Anthony (outside member); Rutgers University; School of Graduate Studies
Date Created2019
Other Date2019-05 (degree)
SubjectPhotographic steganography, Electrical and Computer Engineering, Image steganography, Machine learning
Extent1 online resource (xii, 106 pages) : illustrations
DescriptionIn 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.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-kxd9-y516
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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