Spelling suggestions: "subject:"digital video watermarking"" "subject:"figital video watermarking""
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Digital Video Watermarking Robust to Geometric Attacks and CompressionsLiu, Yan 03 October 2011 (has links)
This thesis focuses on video watermarking robust against geometric attacks and
video compressions. In addition to the requirements for an image watermarking algorithm,
a digital video watermarking algorithm has to be robust against advanced
video compressions, frame loss, frame swapping, aspect ratio change, frame rate change,
intra- and inter-frame filtering, etc. Video compression, especially, the most efficient
compression standard, H.264, and geometric attacks, such as rotation and cropping,
frame aspect ratio change, and translation, are considered the most challenging attacks
for video watermarking algorithms.
In this thesis, we first review typical watermarking algorithms robust against geometric
attacks and video compressions, and point out their advantages and disadvantages.
Then, we propose our robust video watermarking algorithms against Rotation,
Scaling and Translation (RST) attacks and MPEG-2 compression based on the logpolar
mapping and the phase-only filtering method. Rotation or scaling transformation
in the spatial domain results in vertical or horizontal shift in the log-polar mapping
(LPM) of the magnitude of the Fourier spectrum of the target frame. Translation has
no effect in this domain. This method is very robust to RST attacks and MPEG-2
compression. We also demonstrate that this method can be used as a RST parameters
detector to work with other watermarking algorithms to improve their robustness to
RST attacks.
Furthermore, we propose a new video watermarking algorithm based on the 1D
DFT (one-dimensional Discrete Fourier Transform) and 1D projection. This algorithm
enhances the robustness to video compression and is able to resist the most advanced video compression, H.264. The 1D DFT for a video sequence along the temporal domain
generates an ideal domain, in which the spatial information is still kept and the
temporal information is obtained. With detailed analysis and calculation, we choose
the frames with highest temporal frequencies to embed the fence-shaped watermark
pattern in the Radon transform domain of the selected frames. The performance of the
proposed algorithm is evaluated by video compression standards MPEG-2 and H.264;
geometric attacks such as rotation, translation, and aspect-ratio changes; and other
video processing. The most important advantages of this video watermarking algorithm
are its simplicity, practicality and robustness.
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Digital Video Watermarking Robust to Geometric Attacks and CompressionsLiu, Yan 03 October 2011 (has links)
This thesis focuses on video watermarking robust against geometric attacks and
video compressions. In addition to the requirements for an image watermarking algorithm,
a digital video watermarking algorithm has to be robust against advanced
video compressions, frame loss, frame swapping, aspect ratio change, frame rate change,
intra- and inter-frame filtering, etc. Video compression, especially, the most efficient
compression standard, H.264, and geometric attacks, such as rotation and cropping,
frame aspect ratio change, and translation, are considered the most challenging attacks
for video watermarking algorithms.
In this thesis, we first review typical watermarking algorithms robust against geometric
attacks and video compressions, and point out their advantages and disadvantages.
Then, we propose our robust video watermarking algorithms against Rotation,
Scaling and Translation (RST) attacks and MPEG-2 compression based on the logpolar
mapping and the phase-only filtering method. Rotation or scaling transformation
in the spatial domain results in vertical or horizontal shift in the log-polar mapping
(LPM) of the magnitude of the Fourier spectrum of the target frame. Translation has
no effect in this domain. This method is very robust to RST attacks and MPEG-2
compression. We also demonstrate that this method can be used as a RST parameters
detector to work with other watermarking algorithms to improve their robustness to
RST attacks.
Furthermore, we propose a new video watermarking algorithm based on the 1D
DFT (one-dimensional Discrete Fourier Transform) and 1D projection. This algorithm
enhances the robustness to video compression and is able to resist the most advanced video compression, H.264. The 1D DFT for a video sequence along the temporal domain
generates an ideal domain, in which the spatial information is still kept and the
temporal information is obtained. With detailed analysis and calculation, we choose
the frames with highest temporal frequencies to embed the fence-shaped watermark
pattern in the Radon transform domain of the selected frames. The performance of the
proposed algorithm is evaluated by video compression standards MPEG-2 and H.264;
geometric attacks such as rotation, translation, and aspect-ratio changes; and other
video processing. The most important advantages of this video watermarking algorithm
are its simplicity, practicality and robustness.
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Digital Video Watermarking Robust to Geometric Attacks and CompressionsLiu, Yan 03 October 2011 (has links)
This thesis focuses on video watermarking robust against geometric attacks and
video compressions. In addition to the requirements for an image watermarking algorithm,
a digital video watermarking algorithm has to be robust against advanced
video compressions, frame loss, frame swapping, aspect ratio change, frame rate change,
intra- and inter-frame filtering, etc. Video compression, especially, the most efficient
compression standard, H.264, and geometric attacks, such as rotation and cropping,
frame aspect ratio change, and translation, are considered the most challenging attacks
for video watermarking algorithms.
In this thesis, we first review typical watermarking algorithms robust against geometric
attacks and video compressions, and point out their advantages and disadvantages.
Then, we propose our robust video watermarking algorithms against Rotation,
Scaling and Translation (RST) attacks and MPEG-2 compression based on the logpolar
mapping and the phase-only filtering method. Rotation or scaling transformation
in the spatial domain results in vertical or horizontal shift in the log-polar mapping
(LPM) of the magnitude of the Fourier spectrum of the target frame. Translation has
no effect in this domain. This method is very robust to RST attacks and MPEG-2
compression. We also demonstrate that this method can be used as a RST parameters
detector to work with other watermarking algorithms to improve their robustness to
RST attacks.
Furthermore, we propose a new video watermarking algorithm based on the 1D
DFT (one-dimensional Discrete Fourier Transform) and 1D projection. This algorithm
enhances the robustness to video compression and is able to resist the most advanced video compression, H.264. The 1D DFT for a video sequence along the temporal domain
generates an ideal domain, in which the spatial information is still kept and the
temporal information is obtained. With detailed analysis and calculation, we choose
the frames with highest temporal frequencies to embed the fence-shaped watermark
pattern in the Radon transform domain of the selected frames. The performance of the
proposed algorithm is evaluated by video compression standards MPEG-2 and H.264;
geometric attacks such as rotation, translation, and aspect-ratio changes; and other
video processing. The most important advantages of this video watermarking algorithm
are its simplicity, practicality and robustness.
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Digital Video Watermarking Robust to Geometric Attacks and CompressionsLiu, Yan January 2011 (has links)
This thesis focuses on video watermarking robust against geometric attacks and
video compressions. In addition to the requirements for an image watermarking algorithm,
a digital video watermarking algorithm has to be robust against advanced
video compressions, frame loss, frame swapping, aspect ratio change, frame rate change,
intra- and inter-frame filtering, etc. Video compression, especially, the most efficient
compression standard, H.264, and geometric attacks, such as rotation and cropping,
frame aspect ratio change, and translation, are considered the most challenging attacks
for video watermarking algorithms.
In this thesis, we first review typical watermarking algorithms robust against geometric
attacks and video compressions, and point out their advantages and disadvantages.
Then, we propose our robust video watermarking algorithms against Rotation,
Scaling and Translation (RST) attacks and MPEG-2 compression based on the logpolar
mapping and the phase-only filtering method. Rotation or scaling transformation
in the spatial domain results in vertical or horizontal shift in the log-polar mapping
(LPM) of the magnitude of the Fourier spectrum of the target frame. Translation has
no effect in this domain. This method is very robust to RST attacks and MPEG-2
compression. We also demonstrate that this method can be used as a RST parameters
detector to work with other watermarking algorithms to improve their robustness to
RST attacks.
Furthermore, we propose a new video watermarking algorithm based on the 1D
DFT (one-dimensional Discrete Fourier Transform) and 1D projection. This algorithm
enhances the robustness to video compression and is able to resist the most advanced video compression, H.264. The 1D DFT for a video sequence along the temporal domain
generates an ideal domain, in which the spatial information is still kept and the
temporal information is obtained. With detailed analysis and calculation, we choose
the frames with highest temporal frequencies to embed the fence-shaped watermark
pattern in the Radon transform domain of the selected frames. The performance of the
proposed algorithm is evaluated by video compression standards MPEG-2 and H.264;
geometric attacks such as rotation, translation, and aspect-ratio changes; and other
video processing. The most important advantages of this video watermarking algorithm
are its simplicity, practicality and robustness.
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Digital video watermarking using singular value decomposition and two-dimensional principal component analysisKaufman, Jason R. 14 April 2006 (has links)
No description available.
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