RST-Resilient Video Watermarking Using Scene-Based Feature Extraction

<p/> <p>Watermarking for video sequences should consider additional attacks, such as frame averaging, frame-rate change, frame shuffling or collusion attacks, as well as those of still images. Also, since video is a sequence of analogous images, video watermarking is subject to interfram...

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Main Authors: Jung Han-Seung, Lee Young-Yoon, Lee Sang Uk
Format: Article
Language:English
Published: SpringerOpen 2004-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/S1110865704405046
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spelling doaj-c81cf632e6904fd1b200716e31eb33362020-11-24T22:06:28ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802004-01-01200414358092RST-Resilient Video Watermarking Using Scene-Based Feature ExtractionJung Han-SeungLee Young-YoonLee Sang Uk<p/> <p>Watermarking for video sequences should consider additional attacks, such as frame averaging, frame-rate change, frame shuffling or collusion attacks, as well as those of still images. Also, since video is a sequence of analogous images, video watermarking is subject to interframe collusion. In order to cope with these attacks, we propose a scene-based temporal watermarking algorithm. In each scene, segmented by scene-change detection schemes, a watermark is embedded temporally to one-dimensional projection vectors of the log-polar map, which is generated from the DFT of a two-dimensional feature matrix. Here, each column vector of the feature matrix represents each frame and consists of radial projections of the DFT of the frame. Inverse mapping from the one-dimensional watermarked vector to the feature matrix has a unique optimal solution, which can be derived by a constrained least-square approach. Through intensive computer simulations, it is shown that the proposed scheme provides robustness against transcoding, including frame-rate change, frame averaging, as well as interframe collusion attacks.</p>http://dx.doi.org/10.1155/S1110865704405046scene-based video watermarkingRST-resilientradial projections of the DFTfeature extractioninverse feature extractionleast-square optimization problem
collection DOAJ
language English
format Article
sources DOAJ
author Jung Han-Seung
Lee Young-Yoon
Lee Sang Uk
spellingShingle Jung Han-Seung
Lee Young-Yoon
Lee Sang Uk
RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
EURASIP Journal on Advances in Signal Processing
scene-based video watermarking
RST-resilient
radial projections of the DFT
feature extraction
inverse feature extraction
least-square optimization problem
author_facet Jung Han-Seung
Lee Young-Yoon
Lee Sang Uk
author_sort Jung Han-Seung
title RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
title_short RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
title_full RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
title_fullStr RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
title_full_unstemmed RST-Resilient Video Watermarking Using Scene-Based Feature Extraction
title_sort rst-resilient video watermarking using scene-based feature extraction
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2004-01-01
description <p/> <p>Watermarking for video sequences should consider additional attacks, such as frame averaging, frame-rate change, frame shuffling or collusion attacks, as well as those of still images. Also, since video is a sequence of analogous images, video watermarking is subject to interframe collusion. In order to cope with these attacks, we propose a scene-based temporal watermarking algorithm. In each scene, segmented by scene-change detection schemes, a watermark is embedded temporally to one-dimensional projection vectors of the log-polar map, which is generated from the DFT of a two-dimensional feature matrix. Here, each column vector of the feature matrix represents each frame and consists of radial projections of the DFT of the frame. Inverse mapping from the one-dimensional watermarked vector to the feature matrix has a unique optimal solution, which can be derived by a constrained least-square approach. Through intensive computer simulations, it is shown that the proposed scheme provides robustness against transcoding, including frame-rate change, frame averaging, as well as interframe collusion attacks.</p>
topic scene-based video watermarking
RST-resilient
radial projections of the DFT
feature extraction
inverse feature extraction
least-square optimization problem
url http://dx.doi.org/10.1155/S1110865704405046
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