71 research outputs found
Robust Object-Based Watermarking Using SURF Feature Matching and DFT Domain
In this paper we propose a robust object-based watermarking method, in which the watermark is embedded into the middle frequencies band of the Discrete Fourier Transform (DFT) magnitude of the selected object region, altogether with the Speeded Up Robust Feature (SURF) algorithm to allow the correct watermark detection, even if the watermarked image has been distorted. To recognize the selected object region after geometric distortions, during the embedding process the SURF features are estimated and stored in advance to be used during the detection process. In the detection stage, the SURF features of the distorted image are estimated and match them with the stored ones. From the matching result, SURF features are used to compute the Affine-transformation parameters and the object region is recovered. The quality of the watermarked image is measured using the Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and the Visual Information Fidelity (VIF). The experimental results show the proposed method provides robustness against several geometric distortions, signal processing operations and combined distortions. The receiver operating characteristics (ROC) curves also show the desirable detection performance of the proposed method. The comparison with a previously reported methods based on different techniques is also provided
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Digital Watermarking of Images towards Content Protection.
With the rapid growth of the internet and digital media techniques over the last decade, multimedia data such as images, video and audio can easily be copied, altered and distributed over the internet without any loss in quality. Therefore, protection of ownership of multimedia data has become a very significant and challenging issue. Three novel image watermarking algorithms have been designed and implemented for copyright protection. The first proposed algorithm is based on embedding multiple watermarks in the blue channel of colour images to achieve more robustness against attacks. The second proposed algorithm aims to achieve better trade-offs between imperceptibility and robustness requirements of a digital watermarking system. It embeds a watermark in adaptive manner via classification of DCT blocks with three levels: smooth, edges and texture, implemented in the DCT domain by analyzing the values of AC coefficients. The third algorithm aims to achieve robustness against geometric attacks, which can desynchronize the location of the watermark and hence cause incorrect watermark detection. It uses geometrically invariant feature points and image normalization to overcome the problem of synchronization errors caused by geometric attacks.
Experimental results show that the proposed algorithms are robust and outperform related techniques found in literature
Spread spectrum-based video watermarking algorithms for copyright protection
Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can
now benefit from hardware and software which was considered state-of-the-art several years
ago. The advantages offered by the digital technologies are major but the same digital
technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly
possible and relatively easy, in spite of various forms of protection, but due to the analogue
environment, the subsequent copies had an inherent loss in quality. This was a natural way of
limiting the multiple copying of a video material. With digital technology, this barrier
disappears, being possible to make as many copies as desired, without any loss in quality
whatsoever. Digital watermarking is one of the best available tools for fighting this threat.
The aim of the present work was to develop a digital watermarking system compliant with the
recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark
can be inserted in either spatial domain or transform domain, this aspect was investigated and
led to the conclusion that wavelet transform is one of the best solutions available. Since
watermarking is not an easy task, especially considering the robustness under various attacks
several techniques were employed in order to increase the capacity/robustness of the system:
spread-spectrum and modulation techniques to cast the watermark, powerful error correction
to protect the mark, human visual models to insert a robust mark and to ensure its invisibility.
The combination of these methods led to a major improvement, but yet the system wasn't
robust to several important geometrical attacks. In order to achieve this last milestone, the
system uses two distinct watermarks: a spatial domain reference watermark and the main
watermark embedded in the wavelet domain. By using this reference watermark and techniques
specific to image registration, the system is able to determine the parameters of the attack and
revert it. Once the attack was reverted, the main watermark is recovered. The final result is a
high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen
Multiple Content Adaptive Intelligent Watermarking Schemes for the Protection of Blocks of a Document Image
Most of the documents contain different types of information such as white space, static information and dynamic information or mix of static and dynamic information. In this paper, multiple watermarking schemes are proposed for protection of the information content. The proposed approach comprises of three phases. In Phase-1, the edges of the source document image are extracted and the edge image is decomposed into blocks of uniform size. In Phase-2, GLCM features like energy, homogeneity, contrast and correlation are extracted from each block and the blocks are classified as no-information, static, dynamic and mix of static and dynamic information content blocks. The adjacent blocks of same type are merged together into a single block. Each block is watermarked in Phase-3. The type and amount of watermarking applied is decided intelligently and adaptively based on the classification of the blocks which results in improving embedding capacity and reducing time complexity incurred during watermarking. Experiments are conducted exhaustively on all the images in the corpus. The experimental evaluations exhibit better classification of segments based on information content in the block. The proposed technique also outperforms the existing watermarking schemes on document images in terms of robustness, accuracy of tamper detection and recovery
An Adaptive Spread Spectrum (SS) Synchronous Data Hiding Strategy for Scalable 3D Terrain Visualization
International audienceThe diversity of clients in today's network environment compels us to think about solutions that more than satisfy their needs according to their resources. For 3D terrain visualization this translates into two main requirements, namely the scalability and synchronous unification of a disparate data that requires at least two files, the texture image and its corresponding digital elevation model (DEM). In this work the scalability is achieved through the multiresolution discrete wavelet transform (DWT) of the JPEG2000 codec. For the unification of data, a simple DWT-domain spread spectrum (SS) strategy is employed in order to synchronously hide the DEM in the corresponding texture while conserving the JPEG2000 standard file format. Highest possible quality texture is renderable due to the reversible nature of the SS data hiding. As far as DEM quality is concerned, it is ensured through the adaptation of synchronization in embedding that would exclude some highest frequency subbands. To estimate the maximum tolerable error in the DEM according to a given viewpoint, a human visual system (HVS) based psycho-visual analysis is being presented. This analysis is helpful in determining the degree of adaptation in synchronization
Fast image watermarking based on signum of cosine matrix
In the field of image watermarking, the singular value decomposition has good imperceptibility and robustness, but it has high complexity. It divides a host image into matrices of U, S, and V. Singular matrix S has been widely used for embedding and extracting watermark, while orthogonal matrices of U and V are used in decomposition and reconstruction. The proposed signum of cosine matrix method is carried out to eliminate the generation of the three matrices at each block and replace it with a signum of cosine matrix. The proposed signum of cosine matrix is performed faster on the decomposition and reconstruction. The image is transformed into a coefficient matrix C using the signum matrix. The C matrix values are closer to the S value of singular value decomposition which can preserve high quality of the watermarked image. The experimental results show that our method is able to produce similar imperceptibility and robustness level of the watermarked image with less computational time
Symmetry-Adapted Machine Learning for Information Security
Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis
Digital watermarking and novel security devices
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Digital watermark technology in security applications
With the rising emphasis on security and the number of fraud related crimes
around the world, authorities are looking for new technologies to tighten
security of identity. Among many modern electronic technologies, digital
watermarking has unique advantages to enhance the document authenticity.
At the current status of the development, digital watermarking technologies
are not as matured as other competing technologies to support identity authentication
systems. This work presents improvements in performance of
two classes of digital watermarking techniques and investigates the issue of
watermark synchronisation.
Optimal performance can be obtained if the spreading sequences are designed
to be orthogonal to the cover vector. In this thesis, two classes of
orthogonalisation methods that generate binary sequences quasi-orthogonal
to the cover vector are presented. One method, namely "Sorting and Cancelling"
generates sequences that have a high level of orthogonality to the
cover vector. The Hadamard Matrix based orthogonalisation method, namely
"Hadamard Matrix Search" is able to realise overlapped embedding, thus the
watermarking capacity and image fidelity can be improved compared to using
short watermark sequences. The results are compared with traditional
pseudo-randomly generated binary sequences. The advantages of both classes
of orthogonalisation inethods are significant.
Another watermarking method that is introduced in the thesis is based
on writing-on-dirty-paper theory. The method is presented with biorthogonal
codes that have the best robustness. The advantage and trade-offs of
using biorthogonal codes with this watermark coding methods are analysed
comprehensively. The comparisons between orthogonal and non-orthogonal
codes that are used in this watermarking method are also made. It is found
that fidelity and robustness are contradictory and it is not possible to optimise
them simultaneously.
Comparisons are also made between all proposed methods. The comparisons
are focused on three major performance criteria, fidelity, capacity and
robustness. aom two different viewpoints, conclusions are not the same. For
fidelity-centric viewpoint, the dirty-paper coding methods using biorthogonal
codes has very strong advantage to preserve image fidelity and the advantage
of capacity performance is also significant. However, from the power
ratio point of view, the orthogonalisation methods demonstrate significant
advantage on capacity and robustness. The conclusions are contradictory
but together, they summarise the performance generated by different design
considerations.
The synchronisation of watermark is firstly provided by high contrast
frames around the watermarked image. The edge detection filters are used
to detect the high contrast borders of the captured image. By scanning
the pixels from the border to the centre, the locations of detected edges
are stored. The optimal linear regression algorithm is used to estimate the
watermarked image frames. Estimation of the regression function provides
rotation angle as the slope of the rotated frames. The scaling is corrected by
re-sampling the upright image to the original size. A theoretically studied
method that is able to synchronise captured image to sub-pixel level accuracy
is also presented. By using invariant transforms and the "symmetric
phase only matched filter" the captured image can be corrected accurately
to original geometric size. The method uses repeating watermarks to form an
array in the spatial domain of the watermarked image and the the array that
the locations of its elements can reveal information of rotation, translation
and scaling with two filtering processes
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