Results 261 to 270 of about 24,642,685 (320)

High-capacity reversible data hiding in encrypted images based on extended run-length coding and block-based MSB plane rearrangement

Journal of Visual Communication and Image Representation, 2019
In this paper, we propose a novel reversible data hiding method in encrypted images. The proposed method takes full advantage of the spatial correlation in the original images to vacate room for embedding data before image encryption. By jointly using an
Kaimeng Chen, Chinchen Chang
semanticscholar   +1 more source

Data hiding in video

Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348), 2003
We propose a video data embedding scheme in which the embedded signature data is reconstructed without knowing the original host video. The proposed method enables a high rate of data embedding and is robust to motion compensated coding, such as MPEG-2.
J.J. Chae, B.S. Manjunath
openaire   +1 more source

Robust reversible data hiding scheme based on two-layer embedding strategy

Information Sciences, 2020
Robust reversible data hiding (RRDH) prevents the hidden secret information from unintentional modifications. This paper presents a novel RRDH scheme based on two-layer embedding with reduced capacity-distortion trade-off.
Rajeev Kumar, K. Jung
semanticscholar   +1 more source

Reversible Data Hiding

2005
This paper presents a novel reversible data hiding algorithm, which can recover the original image without distortion from the marked image after the hidden data have been extracted. This algorithm utilizes the zero or the minimum point of the histogram and slightly modifies the pixel values to embed data.
openaire   +1 more source

Techniques for data hiding

IBM Systems Journal, 1996
Data hiding, a form of steganography, embeds data into digital media for the purpose of identification, annotation, and copyright. Several constraints affect this process: the quantity of data to be hidden, the need for invariance of these data under conditions where a "host" signal is subject to distortions, e.g., lossy compression, and the degree to ...
W. Bender, D. Gruhl, N. Morimoto, A. Lu
openaire   +1 more source

Hiding data in Tetris

2011 International Conference on Machine Learning and Cybernetics, 2011
Many kinds of data hiding methods using different cover media have been proposed, several papers use games to do steganography recently. Tetris is a famous puzzle game, and this game randomly generates the tetrominoes pieces to the player. In this paper, we proposed a steganography system for the Tetris game through the generated tetromino sequences. A
Zhan-He Ou, Ling-Hwei Chen
openaire   +1 more source

Skewed Histogram Shifting for Reversible Data Hiding Using a Pair of Extreme Predictions

IEEE transactions on circuits and systems for video technology (Print), 2019
Reversible data hiding hides data in an image such that the original image is recoverable. This paper presents a novel embedding framework with reduced distortion called skewed histogram shifting using a pair of extreme predictions.
Suah Kim, Xiaochao Qu, Vasily Sachnev, Hyoung-Joong Kim   +3 more
semanticscholar   +1 more source

Applications for data hiding

IBM Systems Journal, 2000
In an earlier paper, "Techniques for Data Hiding," the overall goals and constraints of information-hiding problem space and a variety of approaches to information hiding in image, audio, and text were described. In this sequel, information-hiding goals and applications are expanded beyond watermarking to encompass the more general concept of ...
W. Bender, W. Butera, D. Gruhl, R. Hwang, F. J. Paiz, S. Pogreb   +5 more
openaire   +1 more source

Dynamic improved pixel value ordering reversible data hiding

Information Sciences, 2019
The existing reversible data hiding (RDH) methods based on improved pixel value ordering (IPVO) use only a small portion of the pixels (e.g., at most six pixels) in a block for embedding data. Our proposed method is a dynamic IPVO RDH, which can flexibly
S. Weng, Y. Shi, Wien Hong, Ye Yao
semanticscholar   +1 more source

HiDDeN: Hiding Data With Deep Networks

European Conference on Computer Vision, 2018
Recent work has shown that deep neural networks are highly sensitive to tiny perturbations of input images, giving rise to adversarial examples. Though this property is usually considered a weakness of learned models, we explore whether it can be ...
Jiren Zhu, Russell Kaplan, Justin Johnson, Li Fei-Fei   +3 more
semanticscholar   +1 more source