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Digital watermarking ieee papers best technical writer resume

Digital watermarking ieee papers

Recently, one of the most straightforward solutions to cope with desynchronization attacks is composed of inserting templates along with the watermark or embedding a periodic watermark pattern into the image. These additional templates [52] [64] are used as artificially embedded references for purposes of resynchronization.

There is insensitive information carried in them. The template-based approach performs the watermark retrieval process by asserting the presence of a watermark and estimating and compensating the severe geometric transformation of the watermarked image for accomplishing resynchronization patterns [41]. Therefore, the registration pattern is identified and offered resilience to geometric attacks [7]. The template-based algorithms introduced in this section all are relevant to adaptive determination in the strength of the templates for constraining the search space.

The contraction of searching space results in being rather susceptible to the credibility of system. Meanwhile, the template is restricted to the number of synchronization points, which tends to be the counterpart of unaccepted false positive probabilities in the parameter estimation of the applied affine transformation.

Also the process of the successful watermark detection relies on the precise detection of the template because the detection error tolerance is unacceptable for the inaccuracy of the detected position. It causes the unwarranted synchronization for shrinking the search space. Although an amount of progress for utilizing template-based watermarking techniques, these ignore the perceptual similarity between the original and watermarked image. The insertion of the watermark and the template should take the embedding position and strength into account carefully.

And besides, the algorithms compromise the data payload of the watermark for keeping the restricted fidelity of the original image after the embedding process, since the embedded template tries to decrease the number of embedded information that consist of the template to guarantee synchronization and avoid potential visible artifacts. In addition, security aspect has been paid little regard, because these algorithms are particularly vulnerable to template removal attacks [23] [25] [7].

If these templates are provided with characteristic features of independence from the host image, then the specific characteristics can be exploited to destruct the synchronization pattern. In another word, the templates are used to be inserted as pseudorandom noise patterns and some specific operations, for example filtering operators, can filter potentially out the local maxima.

Then, the applied templates are eliminated easily by the malicious attack and the applied various geometric transformations are unable to be recognized during the template detection process. In brief, the major limitation is that this kind of approach has a severe influence on the resistance of affine transformations confronting with threats and risks of the template attack. Self-synchronizing watermarks [29] [21] are susceptible to removal or estimation attacks in much the same way as template-based methods, because an attacker can use knowledge about the watermark's periodic tiling to remove it.

For example, attackers can easily remove peaks in the autocorrelation function or the frequency domain by filtering in the spatial or the frequency domain, thus rendering the watermark vulnerable to subsequent geometric attacks. Another solution consists in embedding the watermark in a geometrical invariant subspace.

In [12] , it suggested using histogram specification to hide a watermark invariant to geometrical distortions. In [60] and [38] , they proposed a watermarking scheme based on the Fourier-Mellin transform [39]. A rotation, scale and translation invariant domain is obtained using the log-polar mapping LPM and the Fourier transform invariance properties to translations. In the resulting log-polar map, rotations and scaling come down to translations. In practice, this solution can be implemented for simple affine transformations, but it is inapplicable as soon as the image undergoes local geometrical deformations.

Moreover, problems of approximation due to the discrete nature of the images, plus the reduction of the embedding space make the watermark weakly resistant to low-pass filtering and lossy compression. Alghoniemy and Tewfik [2] present another approach where the watermarking space is defined as a canonical, normalized space based on the geometric image moments.

The watermark is embedded in this space, and then the inverse transformation is applied to obtain the final watermarked image. During detection, the moments are calculated again and used to estimate the normalization parameters. Once the image is normalized, the watermark can be detected.

Rather than embedding the watermark in an invariant subspace, Solachidis and Pitas propose creating a self-similar watermark, and to embed it then into the DFT domain [63]. Thus, their method is robust to translation, since it does not affect the DFT magnitude. Since the watermark is made up of identical sectors, the detection is possible even after a degree rotation. The self-similar properties of the watermark also allows for the reduction of the number of different frequency sampling steps where the detection should be performed when the image has been cropped and scaled.

Feature-based watermarking has raised a number of available algorithms over the last few years. For solving watermark synchronization problems, featureregion detection is the preferred strategy to resist against local geometric distortions. Generally speaking, content-based synchronization watermarking schemes follow the same basic process: detected feature points are localized at the local maxima while non-maxima suppression that eliminates pixels that are not local maxima, and the final set of features is determined by analysis of threshold.

Afterwards, extracted feature points are applied to identify regions for watermark insertion in the host image. At the receiver side, the feature points are detectible without synchronization error. The observation of feature-based synchronization has resulted in various algorithms known as region-based watermarking [22] [35] [36] [61] [62] ] [73] [74] [75]. The feature points-based approach is a technique using localized watermarking algorithms.

It discovers the watermark using stable feature points of images, where the watermark is independently inserted into the corresponding each local region [29]. Hence the feature-based process can be invariant to local geometrical deformations so that it is an encouraging approach to solve the robustness against geometrical deformations in the watermarking scheme with blind detection.

In [7] , it extracted feature points of the host image using Harris detector and produced a Delaunay tessellation on the group of stable feature points. Then, the watermark was inserted in each triangle of the tessellation. But the Harris feature points were not invariant to scaling [46] so that the approach is not resistant to the attack of scaling. In [69] , it produced a feature extraction process named Mexican Hat wavelet scale interaction.

Image normalization was individually exploited to unoverlapping image circles with the firm radius and the center at the obtained feature points. In spite of the fact that the system displays experimentally the robustness to the majority of attacks, it is attackable to scaling transforms because these transform can cause the alterations of content for two blocks in the image circles with a firm radius.

In [35] , it presented the Harris feature points from the image with the normalized scale and inserted the watermark within each disk region in the center at the localized stalest Harris points and firm radius. The presented method can be resistant to global geometrical transformations, including scaling, rotation and moderate translation.

Nevertheless, the presented scheme cannot be robust against cropping because the normalization of scale may be sensitive to cropping in nature. Recently, many researchers have turned interest orientation to the resynchronization of watermark using the scale invariant feature detectors relied on the scale-space theory in the pattern recognition fields, such as Harris-Laplace, scale invariant feature transform SIFT [33]. In [33] , the SIFT feature is exploited to produce the circular patches as the inserting modules.

The rectangular watermark is transformed to be a polar-mapped watermark, and inversely polar-mapped to determine inserting modules before watermark insertion. The watermark correspondence detection is achieved by the circular convolution. The invariant watermark of rotation is obtained by the translation characteristic of the polar-mapped circular pads. In [33] , Harris-Laplace approach is applied to extract the scale invariant feature points relied on the scale selection theory using Harris corner points.

The watermark is inserted after affine the normalization according to the local characteristic scale at each feature point. The characteristic scale is defined by the scale, where the normalized scale-space representation of an image achieves a maximum value, and the characteristic orientation relied on the angle of the dominant axis of an image. In [22] , a robust watermarking approach was proposed combining Tchebichef moments and the local circular regions LCRs.

In [62] , the affine invariant point detector [46] was discussed to detect feature points. For a chosen feature point, an elliptical feature region viz. Before embedding, the watermark, it is geometrically transformed into an elliptical pattern according to the shape of the region.

This method has a modest robustness and provides a potential idea for resistance against complicated geometric distortions. With the rapid proliferation of globally-distributed computer network technologies and popularity of multimedia systems, fashionable and economical digital recording and storage devices have made it possible to construct the platform, which has considerably make it easy to not only acquire, represent, replicate, distribute, and transmit multimedia contents in digital formats without degradation of quality, but also to manipulate them.

However, the transmission of information over various networks is often unsafe. This lack of security can be critical depending on the nature of the transmitted media. This issue gave rise to digital watermarking, a research field which deals with the process of embedding information into digital data in an inconspicuous manner.

This in turn enables information security for various multimedia applications including copyright protection. In this paper, different watermarking techniques have been reviewed and analyzed. This is based on image processing in spatial and transform domain. Different techniques using singular value decomposition and discrete wavelet transform in transform domain have been reviewed. Additionally, the analysis of these techniques has been represented in the form of tables considering different factors of watermarking like embedding imperceptibility, capacity, security, robustness and false positive.

It can be concluded that various attacks techniques are used to the assessment of watermarking systems, which supplies an automated and fair analysis of substantial watermarking methods for chosen application areas. Furthermore, watermarking algorithms robust against the geometrical distortions have been the focus of research. Inicio Journal of Applied Research and Technology. Descargar PDF. Abdalla 3. Under a Creative Commons license.

Moreover, it is concluded that various attacks operators are used for the assessment of watermarking systems, which supplies an automated and fair analysis of substantial watermarking methods for chosen application areas. Texto completo. Figure 1. Nonblind watermarking framework. Figure 2. Blind watermarking framework. Figure 3. Alghoniemy, A.

Geometric distortion correction in image watermarking. Geometric distortion correction through image normalization. IEEE Int. Multimedia and Expo, 3 , pp. Progressive quantized projection approach to data hiding. Alvarez, G. Analysis of pilot- based synchronization algorithms for watermarking of still images.

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Signal Process, 89 , pp. Dong, N. Affine transformation resistant watermarking based on image normalization. Proceedings of International Conference on Image Processing, 3 , pp. Journal of Applied Research and Technology, 10 ,.

Herrigel, S. Voloshynovskiy, Y. The watermark template attack, pp. Holliman, N. Memon, M. Watermark estimation through local pixel correlation, , pp. Considerations on watermarking security, pp. Kim, H. Choi, K. Lee, T. An asymmetric watermarking system with many embedding watermarks corresponding to one detection watermark. Watermarking Resisting to Translation, Rotation, and Scaling. Kutter, S. Bhattacharjee, T. Toward second generation watermarking schemes.

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Signal Process, 54 , pp. Solachidis, I. Self-similar ring shaped watermark embedding in 2-D DFT domain. Stankovic, I. Djurovic, I. Image Processing, 10 , pp. Su, B. Taboada, P. Larralde, T. Brito, L. Vega-Alvarado, R. Diaz, E. Galindo, G. Images acquisition of multiphase dispersions in fermentation processes. Journal of Applied Research and Technology, 1 ,. Takahashi, R. Nishimura, Y. Multiple watermarks for stereo audio signals using phase-modulation techniques.

Tang, H. A feature-based robust digital image watermarking scheme. Signal Process, 51 , pp. Tao, B. Image Processing, 4 , pp. Erdeljan, L. Imre, D. Yu, Z. A robust blind image watermarking scheme based on feature points and RS- invariant domain. Yuan, H. Ling, Z. Lu, Y. Image content- based watermarking resistant against geometrical distortions.

Zheng, Y. Liu, J. A survey of RST invariant image watermarking algorithms. ACM Comput. Kurak, J. A method for signature casting on digital images. Zhang, Y. Li, X. Cruz-Ramos, R. Reyes-Reyes, M. Normalized Cross Correlation NC. Page 2. The International Watermarking techniques can complement encryption by embedding a secret imperceptible signal, a watermark , directly into the clear data in such a way.

Page Where are Watermarks Used Watermarks have been used or proposed in: digital cameras. Digital watermarking is the process of encoding hidden Copyright information in an image by A review of watermarking principles and practices Semantic free download However, after receipt and subsequent decryption, the data is no longer protected and is in the clear.

Watermarking compliments encryption. A digital watermark is Digital Watermarking Semantic Scholar free download In the present review paper, the author is pointing out challenges and issues which occurred while this technique is applied. TheAfter that, watermark i. This technique, i. The watermarking solution promise to protect your images by. The watermark acts as an instrument to connect the toy a real world object to a digital entity such as a computer or the Internet.

Detecting the watermark is akin From Weak to Strong Watermarking Cryptology ePrint Archive free download We stress that in these latter results, we explicitly do not construct secure watermarking schemes from scratch. Instead, we show that watermark designers can Principles of Digital Image and Video Watermarking free download watermarked data, even after copying and Media authentication fragile watermarking. On the Effectiveness of Visible Watermarks CVF Open Access free download Visible watermarks are used extensively by photogra- phers and stock content services to mark and protect dig- ital photos and videos shared on the web.

Such Watermarking software in practical applications Bulletin of free download This leads us to the topic of attacks, that is operations which result in re- moving digital watermark from digitally watermarked data. Robust watermarks are Screen Watermarking for Data Theft Investigation and Attribution free download We introduce a content-agnostic watermarking approach for textual information displayed on computer screens.

The watermark is imperceptible during regular use. Watermarking www-inst. The watermark is present everywhere! Early aproaches: Spatial Domain Embedding. Original idea: LSB Lossless Visible Watermarking CECS free download In traditional visible watermarking and invisible watermarking , watermarking is performed by embedding a digital watermark signal into a digital host signal Watermarking security: theory and practice HAL-Inria free download 2 Watermarking security: theory and practice.

But the difference image looks interesting. Page 5. This involves modifying. Watermarking , which also contains a secret message within the host data, is a particular form of data hiding with a different purpose Principles of Digital Watermarking free download A systems false negative rate is the frequency with which it is expected to NOT detect watermarks in watermarked works.

Random, watermarked work. Robust Mesh Watermarking Princeton Graphics free download Robust watermarks must be able to survive a variety of attacks , including resizing, cropping, and filtering. For resilience to such attacks, recent watermarking A Review on Digital Watermarking and Its Techniques free download If a digital watermark distorts the carrier signal in a way that it becomes perceivable, it is of no use.

Communication-based models of watermarking. Geometric models of watermarking. A visible watermark on a file or image is very similar to a corporations logo on its letterhead. It is Text Watermarking for Text Document Copyright Protection free download Text watermarking is a process to embed a watermark into text document. The watermarks can be divided into two types: visible and invisible, and is associated Digital watermarks for copyright protection Research Online free download Figure 4: a A host image and b its watermarked version.

Figure 5: The watermark used in Figure 4. Page 8. Digital Watermarks for An Entropy Masking Model for Multimedia Content free download A digital watermark , or watermark in general is an invisible mark inserted in digital media such as digital images, audio and video so that it can later be detected.

Watermarking Cryptographic Capabilities People MIT free download In this work, we study the problem of watermarking various cryptographic programs such as pseudorandom function PRF evaluation, decryption, and signing.

Mohanty free download Digital Watermarking is the process that embeds data called a watermark into a multimedia object such that watermark can be detected or extracted later to make Protecting Iris Images through Asymmetric Digital Watermarking free download Protecting Iris Images through Asymmetric Digital Watermarking. Watermarking Techniques for Intellectual Property Protection free download This paper establishes principles of watermarking - based IP protection, where a watermark is a mechanism for identi- fication that is i nearly invisible to human Design and implementation of spatial data watermarking free download data watermarking service SDWS system which can provide a secure framework for Keywords spatial data transaction; digital watermarking ; watermarking Multiresolution watermarking for images and video Microsoft free download Early work on digital watermarking focused on information hiding in the spatial domain.

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Keywords Watermark ; Discrete Cosine Transform. In transform domain watermarking algorithms based on DCT,DWT, discrete Hadamard transform, Software Watermarking: Models and Dynamic Embedding free download Finally, we propose a new software watermarking technique in which a dynamic graphic watermark is stored in the execution state of a pro- gram. Screen Watermarking for Data Theft Investigation and Attribution free download We introduce a content-agnostic watermarking approach for textual information displayed on computer screens.

Properties of Digital Image Watermarking IRep IIUM free download Digital image watermarking techniques stand on embedding a host image with information which is called watermark , then the watermarked image will be.

Wavelet-based digital image watermarking University of free download Spatial domain watermarking is easy to implement and requires no original image for watermark detection. Asim Naveed Yasir Saleem Advanced Watermarking and its Applications Fraunhofer IIS free download Watermarking is the imperceptible transmission of additional data along with some cover data often multimedia data by so-called watermarks. It offers means The Use of Digital Watermarking for Intelligence SciELO free download Digital watermarking is a promising technology to embed information as unperceivable signals in digital contents.

Various watermarking techniques have been Review on Semi-Fragile Watermarking Algorithms for MDPI free download 2 semi-fragile watermarks are primarily used to certificate the integrity and authenticity of image data. The fragile watermark is usually used to A Survey of Digital Watermarking Techniques, Applications free download watermarking system is defined as the maximum amount of information that can be embedded in the cover work. The number of watermark bits in a message in Forensic Watermarking cloudfront.

Implementation Considerations for. Streaming Media. Created and Approved by the Streaming Video Alliance. July 1 Simple digital watermarking technique consists of two modules watermark embedding module and watermark detection Survey of watermarking techniques Lehigh Preserve free download Watermark is a very old technique. It appeared nearly years ago with the art of handmade papermaking. Optimized for Short-Form and Long-Form content tracking.

Protocols for Watermark Verification School of Engineering free download A watermark is a signal added to the digital image that can later be extracted or detected to make an assertion about the image. By its very nature, a watermark modifies the item being watermarked : it inserts an indelible mark in the Digital Watermarking Applications and Techniques: A Brief free download For a strong watermark embedding, a good watermarking technique is needed to be applied.

Watermark can be embedded either in spatial or frequency domain. Inge J. Cox, Matthew L. Miller, Jeffrey A. Bloom, Jessica Fridrich, and Ton Kalker. Imagine if you had an illegal copy of an image that you would like to Imperceptible Digital Image Watermarking free download Digital watermarking is a process of embedding information into a digital media such as image, audio, text etc. Watermarking is similar to steganography. Both will Digital Image Watermarking in Transform Domains free download 4 The watermarking technique should allow embedding and extraction of more than one watermark each independent of the other capacity.

This thesis presents A Blind Watermarking Technique for Color Image based on free download Abstract Digital watermarking is a method for protecting copyrighted materials such as digital images. This paper presents a new color watermark embedding Basics of Watermarking Stanford University free download Real-time screen watermarking using overlaying layer SBA free download In this paper a method for watermarking the screen image, that can be used in forensic investigations, is presented.

The Classification of Watermarking Based upon Various ijcait free download Visible watermark embedding algorithms are less computationally complex. The watermarked image cannot with stand the signal processing attacks, like the A New Watermarking Method for 3D Model based on Integral free download Index Terms Semi-fragile watermark , 3D model watermark - ing, Integral invariants.

Digital watermarking has been studied over many years Digital Image Watermarking using Discrete Wavelet irjet free download Section III contains DWT watermarking scheme, proposed techniques for watermark embedding and extraction and section IV contains experimental results. The data inserted is the watermark. This watermarking doesnt give any mark on the An Image Forensic Scheme with Robust and Fragile free download 1 Through a dual watermarking approach, the proposed scheme can achieve Keywords: Image Forensics, Fragile and Robust Watermarking , Digital Image Watermarking Techniques And Its IJERT free download Watermark extraction uncovers the watermark in watermarked images, a technique usually applicable in verification watermarks.

Abstract Watermarking technology, answering TV industry requirements, 1 has emerged in trials over the last few years. While the.

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The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research.

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Management essay editing site Cheng, C. Therefore, the registration pattern is identified and offered resilience to geometric attacks [7]. It is essential to define the criteria of a watermarking system for the comparison results against equivalence of group of the assessment attained by assessing the performance of other watermarking methods. However, the transmission of information over various networks is often unsafe. Test based. Before embedding, the watermark, it is geometrically transformed into an elliptical pattern according to the shape of the region. Although an amount of progress for utilizing template-based watermarking techniques, these ignore the perceptual similarity between the original and watermarked image.
Email resume body Moulin, J. The insertion of the watermark and the template should take the embedding position and strength into account carefully. This method has a modest robustness and provides a potential idea for resistance against complicated geometric distortions. A Robust Color Image Watermarking Algorithm with Various Attacks free download The increased and widespread usage of template of a professional resume multimedia has aroused great concerns regarding issues such as copyright protection, copy control and proof of ownership. This is a preview of subscription content, access via your institution. In addition, suspicious perceptible artifacts may introduce a watermark in existence, and perhaps its precise location being detected from host media. These formats are spreading very fast over the internet Secure and Robust Digital Image Watermarking using Stegnography free download This paper presents a chaotic encryption-based blind digital image watermarking technique applicable to both grayscale and color images.
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LITERATURE REVIEW OF FASHION

If the robustness of global affine transformations is a little or a lot a resolved problem, the local random transformations integrated by Stirmark always remain an open issue almost for all methods. The random bending attacks exploit the background that the human visual system is insensitive towards local affine modifications and shifts.

Thus, the locally shifted, rotated and scaled pixels are without distortions in significant visual aspects. The thesis will also discuss dedicated attacks, which intend to test the efficiencies of proposed algorithms. Cryptographic attacks are quite equivalent to the attacks applied in cryptography. There are the seriously forced attacks which intend to discover secret information using the exhaustive searches.

Ever since numerous watermarking systems utilize a secret key, it is greatly significant to use keys with a safe length. In addition, another attack is the so-called Oracle attacks in this category [13] and [53] , which is able be applied to produce a non-watermarked image while a device of a watermark detector is attainable.

The protocol attacks intend to attack the definition of the watermarking applications. The protocol attack was introduced by [19]. They present the structure of unidirectional watermark and demonstrate that watermarks requisite for being non-invertible in applications of copyright protection.

The concept of inversion comprises of the truth that attackers who have a copy of the stego contents can represent that the data also includes the attackers' watermark using subtracting to his own watermark information. The activities can produce an ambiguity's condition with respect to the authentic ownership of the contents.

The prerequisite of non-inevitability on the watermarking system suggests that it should not be potential to detect or extract a watermark from non-watermarked images. The attackers may change the watermarked image nearby vertically and horizontally, or remove an entire line of pixels, to distort the watermark information delivered.

For the embedding watermarks in the VQ or DCT domains, image shifting may result in the algorithm of extracting the watermark to miss the resynchronization of the watermarked images. How to acquire an acceptable quality in the watermarked image and to preserve the capability for recovering the embedded watermark with the image shifting scheme is another topic for robust watermarking Although the aforementioned categorization makes it potential to have an understandable segregation between the different kinds of attacks, it is unavoidable to the reminder that a malicious attacker usually uses not only a single attack, but rather a combination of various attacks at the moment.

Such a probability is forecasted in the Stirmark benchmark, where all geometric transformations are practically accompanied by the attack of lossy compression. Spatial domain watermarking is attractive because it provides a better intuition on how to attainan optimal tradeoff between robustness, capacity and imperceptibility. Thus, coming up with public spatial domain algorithms which survive a broad range of manipulations is an important issue.

However, the most serious problem of spatial domains is the weakness of robustness. Therefore, watermarking schemes in spatial domains usually are used singly. In electronics, control systems engineering, and statistics, frequency domain is a term used to describe the domain for analysis of mathematical functions or signals with respect to frequency, rather than time. A frequency-domain representation can also include information on the phase shift that must be applied to each sinusoid in order to be able to recombine the frequency components to recover the original signal.

In this section, the concept of Singular Value Decomposition and Discrete Wavelet Transform are introduced for decomposing images. The singular value decomposition SVD of a matrix with real or complex entries is one of the fundamental tools of mathematics.

This type of algorithms has proven to be robust in watermarking systems. It was given detailed properties and other applications for SVD in [34]. It is noted that the SVD applies more generally to complex-valued rectangular matrices, while we restrict our discussion to real-valued, square matrices.

The singular value decomposition of A is represented by,. The columns of U denoted by U i , s are called the left singular vectors while the columns of V denoted by V i , s are called the right singular vectors of A.

In [42] , the watermarking scheme is fundamentally flawed algorithm, this is because one attacker can always claim that this watermark was the embedded one and he can claim ownership of the watermarked image, using the singular vectors of any fake watermark in the detection stage. For correcting fault scheme, a SVD-based watermarking algorithm, which explores the optimal scaling factors of watermark embedding, is presented.

Multiresolution image representations using Discrete Wavelet Transform DWT have received wide range of attention in the recent years. It is a fast pyramidal algorithm and an efficient mathematical tool that decomposes an image into hierarchical subbands. Each sub-band is logarithmically spaced in the frequency domain.

DWT separates an image into a lower resolution and labels the resulting subimages. LL the approximation which is the coarse overall shape, covers the low-frequency components that contain most of the energy in the image and LH horizontal details , HL vertical details and HH diagonal details which represent higher-frequency detailed information have the finer scale wavelet coefficients according to the filters used to generate the sub-image.

The size of the input data reduces gradually. The size at each succeeding octave is one-fourth the size of the previous one. This process is repeated several times until the desired final scale is obtained as shown in Figure 3. The Figure shows the sketch of the decomposition of an image in three resolution levels through DWT.

In the analysis of reconstruction, the inverse DWT is performed by a similar structure with the corresponding synthesis subimages, consisting of an inverse the approximation coefficients and the detail coefficients. This feature makes the watermark more robust in comparison with spatial methods against various distortions. The applications of DWT are efficient due to two important reasons. One: it has the irregular distribution of the inverse transform value in a pyramidal wavelet domain.

Two: it has the low linear complexity which requires lower computational cost O n when compared with the computational cost consumed by Fourier and cosine transforms O n log n. Watermarking algorithms robust to the geometrical distortions have been the focus of research [81]. Most of the proposed geometrical transform invariant algorithms are actually only RST invariant.

Also the systematic analysis of the watermarking algorithm performance under geometrical distortion has begun to draw great attention. Most of these efforts confine to theoretically analyzing and quantifying the effect of the global affine transform to the performance of the watermarking algorithms. Local distortions are more and more regarded as a necessary test scenario in benchmarking software. However, it is difficult to theoretically analyze its effect on watermark detection due to its complexity.

Exhaustive search technique [31] is one of commonly used candidate approaches to coping with the watermark desynchronization problem. This approach performs the process of watermark detection over a training sequence containing each pilot geometrical inverse deformation. The watermark is recovered by searching each hypothetical distortion parameter. Obviously, it seems to be difficult to efficiently evaluate deformation parameters for the absence of the original image [1] [3].

Also, the high computational complexity of performing the method is intractable. It is feasible that exploring spaces are precluded in a reasonable subset of parameters. In this way, the limitation of the search space's size constrains essential degradation of perceptual quality in watermarked images. However, the restriction of search space suffers from unacceptable effects [36] that it can increase more errors of the synchronizer outcome, and the dramatically proliferated false positive probability because of the geometrical deformation and the interpolation errors [4].

In [6] and [45] , the stochastic analysis is used as the further discussion. It is shown that the implementation of random bending attacks in Stirmark enlarges the searching space and increases computation complicatedly for exhaustive search detector.

Recently, one of the most straightforward solutions to cope with desynchronization attacks is composed of inserting templates along with the watermark or embedding a periodic watermark pattern into the image. These additional templates [52] [64] are used as artificially embedded references for purposes of resynchronization.

There is insensitive information carried in them. The template-based approach performs the watermark retrieval process by asserting the presence of a watermark and estimating and compensating the severe geometric transformation of the watermarked image for accomplishing resynchronization patterns [41]. Therefore, the registration pattern is identified and offered resilience to geometric attacks [7].

The template-based algorithms introduced in this section all are relevant to adaptive determination in the strength of the templates for constraining the search space. The contraction of searching space results in being rather susceptible to the credibility of system.

Meanwhile, the template is restricted to the number of synchronization points, which tends to be the counterpart of unaccepted false positive probabilities in the parameter estimation of the applied affine transformation. Also the process of the successful watermark detection relies on the precise detection of the template because the detection error tolerance is unacceptable for the inaccuracy of the detected position. It causes the unwarranted synchronization for shrinking the search space.

Although an amount of progress for utilizing template-based watermarking techniques, these ignore the perceptual similarity between the original and watermarked image. The insertion of the watermark and the template should take the embedding position and strength into account carefully. And besides, the algorithms compromise the data payload of the watermark for keeping the restricted fidelity of the original image after the embedding process, since the embedded template tries to decrease the number of embedded information that consist of the template to guarantee synchronization and avoid potential visible artifacts.

In addition, security aspect has been paid little regard, because these algorithms are particularly vulnerable to template removal attacks [23] [25] [7]. If these templates are provided with characteristic features of independence from the host image, then the specific characteristics can be exploited to destruct the synchronization pattern.

In another word, the templates are used to be inserted as pseudorandom noise patterns and some specific operations, for example filtering operators, can filter potentially out the local maxima. Then, the applied templates are eliminated easily by the malicious attack and the applied various geometric transformations are unable to be recognized during the template detection process.

In brief, the major limitation is that this kind of approach has a severe influence on the resistance of affine transformations confronting with threats and risks of the template attack. Self-synchronizing watermarks [29] [21] are susceptible to removal or estimation attacks in much the same way as template-based methods, because an attacker can use knowledge about the watermark's periodic tiling to remove it.

For example, attackers can easily remove peaks in the autocorrelation function or the frequency domain by filtering in the spatial or the frequency domain, thus rendering the watermark vulnerable to subsequent geometric attacks. Another solution consists in embedding the watermark in a geometrical invariant subspace. In [12] , it suggested using histogram specification to hide a watermark invariant to geometrical distortions.

In [60] and [38] , they proposed a watermarking scheme based on the Fourier-Mellin transform [39]. A rotation, scale and translation invariant domain is obtained using the log-polar mapping LPM and the Fourier transform invariance properties to translations.

In the resulting log-polar map, rotations and scaling come down to translations. In practice, this solution can be implemented for simple affine transformations, but it is inapplicable as soon as the image undergoes local geometrical deformations.

Moreover, problems of approximation due to the discrete nature of the images, plus the reduction of the embedding space make the watermark weakly resistant to low-pass filtering and lossy compression. Alghoniemy and Tewfik [2] present another approach where the watermarking space is defined as a canonical, normalized space based on the geometric image moments.

The watermark is embedded in this space, and then the inverse transformation is applied to obtain the final watermarked image. During detection, the moments are calculated again and used to estimate the normalization parameters. Once the image is normalized, the watermark can be detected. Rather than embedding the watermark in an invariant subspace, Solachidis and Pitas propose creating a self-similar watermark, and to embed it then into the DFT domain [63].

Thus, their method is robust to translation, since it does not affect the DFT magnitude. Since the watermark is made up of identical sectors, the detection is possible even after a degree rotation. The self-similar properties of the watermark also allows for the reduction of the number of different frequency sampling steps where the detection should be performed when the image has been cropped and scaled.

Feature-based watermarking has raised a number of available algorithms over the last few years. For solving watermark synchronization problems, featureregion detection is the preferred strategy to resist against local geometric distortions. Generally speaking, content-based synchronization watermarking schemes follow the same basic process: detected feature points are localized at the local maxima while non-maxima suppression that eliminates pixels that are not local maxima, and the final set of features is determined by analysis of threshold.

Afterwards, extracted feature points are applied to identify regions for watermark insertion in the host image. At the receiver side, the feature points are detectible without synchronization error. The observation of feature-based synchronization has resulted in various algorithms known as region-based watermarking [22] [35] [36] [61] [62] ] [73] [74] [75].

The feature points-based approach is a technique using localized watermarking algorithms. It discovers the watermark using stable feature points of images, where the watermark is independently inserted into the corresponding each local region [29].

Hence the feature-based process can be invariant to local geometrical deformations so that it is an encouraging approach to solve the robustness against geometrical deformations in the watermarking scheme with blind detection. In [7] , it extracted feature points of the host image using Harris detector and produced a Delaunay tessellation on the group of stable feature points. Then, the watermark was inserted in each triangle of the tessellation.

But the Harris feature points were not invariant to scaling [46] so that the approach is not resistant to the attack of scaling. In [69] , it produced a feature extraction process named Mexican Hat wavelet scale interaction. Image normalization was individually exploited to unoverlapping image circles with the firm radius and the center at the obtained feature points.

In spite of the fact that the system displays experimentally the robustness to the majority of attacks, it is attackable to scaling transforms because these transform can cause the alterations of content for two blocks in the image circles with a firm radius.

In [35] , it presented the Harris feature points from the image with the normalized scale and inserted the watermark within each disk region in the center at the localized stalest Harris points and firm radius. The presented method can be resistant to global geometrical transformations, including scaling, rotation and moderate translation.

Nevertheless, the presented scheme cannot be robust against cropping because the normalization of scale may be sensitive to cropping in nature. Recently, many researchers have turned interest orientation to the resynchronization of watermark using the scale invariant feature detectors relied on the scale-space theory in the pattern recognition fields, such as Harris-Laplace, scale invariant feature transform SIFT [33].

In [33] , the SIFT feature is exploited to produce the circular patches as the inserting modules. The rectangular watermark is transformed to be a polar-mapped watermark, and inversely polar-mapped to determine inserting modules before watermark insertion. The watermark correspondence detection is achieved by the circular convolution. The invariant watermark of rotation is obtained by the translation characteristic of the polar-mapped circular pads.

In [33] , Harris-Laplace approach is applied to extract the scale invariant feature points relied on the scale selection theory using Harris corner points. The watermark is inserted after affine the normalization according to the local characteristic scale at each feature point. The characteristic scale is defined by the scale, where the normalized scale-space representation of an image achieves a maximum value, and the characteristic orientation relied on the angle of the dominant axis of an image.

In [22] , a robust watermarking approach was proposed combining Tchebichef moments and the local circular regions LCRs. In [62] , the affine invariant point detector [46] was discussed to detect feature points. For a chosen feature point, an elliptical feature region viz.

Before embedding, the watermark, it is geometrically transformed into an elliptical pattern according to the shape of the region. This method has a modest robustness and provides a potential idea for resistance against complicated geometric distortions. With the rapid proliferation of globally-distributed computer network technologies and popularity of multimedia systems, fashionable and economical digital recording and storage devices have made it possible to construct the platform, which has considerably make it easy to not only acquire, represent, replicate, distribute, and transmit multimedia contents in digital formats without degradation of quality, but also to manipulate them.

However, the transmission of information over various networks is often unsafe. This lack of security can be critical depending on the nature of the transmitted media. This issue gave rise to digital watermarking, a research field which deals with the process of embedding information into digital data in an inconspicuous manner.

This in turn enables information security for various multimedia applications including copyright protection. In this paper, different watermarking techniques have been reviewed and analyzed. This is based on image processing in spatial and transform domain. Different techniques using singular value decomposition and discrete wavelet transform in transform domain have been reviewed.

Additionally, the analysis of these techniques has been represented in the form of tables considering different factors of watermarking like embedding imperceptibility, capacity, security, robustness and false positive. It can be concluded that various attacks techniques are used to the assessment of watermarking systems, which supplies an automated and fair analysis of substantial watermarking methods for chosen application areas.

Furthermore, watermarking algorithms robust against the geometrical distortions have been the focus of research. Inicio Journal of Applied Research and Technology. Descargar PDF. Abdalla 3. Under a Creative Commons license. Moreover, it is concluded that various attacks operators are used for the assessment of watermarking systems, which supplies an automated and fair analysis of substantial watermarking methods for chosen application areas.

Texto completo. Figure 1. Nonblind watermarking framework. Figure 2. Blind watermarking framework. Figure 3. Alghoniemy, A. Geometric distortion correction in image watermarking. Geometric distortion correction through image normalization. IEEE Int. Multimedia and Expo, 3 , pp.

Progressive quantized projection approach to data hiding. Alvarez, G. Analysis of pilot- based synchronization algorithms for watermarking of still images. Signal Processing: Image Communication, 17 , pp. Andreas, D. Effectiveness of exhaustive search and template matching against watermark desynchronization. Bas, J. Chassery, B. Geometrically invariant watermarking using feature point. Christian, D. Jana, L. Transparency benchmarking on audio watermarks and steganography,.

Coltuc, P. Robust watermarking by histogram specification. Image Processing, 2 , pp. Cox, J. Some general methods for tampering with watermarks. IEEE J. Selected Areas Communi. Cox, M. Miller, J. Digital Watermarking, Morgan Kaufman, ,. Bloom, J. Fridrich, T. Digital Watermarking and Steganography, , pp. A review of watermarking and the importance of perceptual modeling, ,. Secure spread spectrum watermarking for images, audio and video, pp. Kilian, F.

Leighton, T. Secure spread spectrum watermarking for multimedia. Craver, N. Memon, B. Yeo, M. Can invisible watermark resolve rightful ownerships. Deguillaume, G. Csurka, T. Countermeasures for unintentional and intentional video watermarking attacks, ,. Delannay, B. Deng, X. Gao, X.

Li, D. A local Tchebichef moments-based robust image watermarking. Signal Process, 89 , pp. Dong, N. Affine transformation resistant watermarking based on image normalization. Proceedings of International Conference on Image Processing, 3 , pp. Journal of Applied Research and Technology, 10 ,. Herrigel, S.

Voloshynovskiy, Y. The watermark template attack, pp. Holliman, N. Memon, M. Watermark estimation through local pixel correlation, , pp. Considerations on watermarking security, pp. Kim, H. Choi, K. Lee, T. An asymmetric watermarking system with many embedding watermarks corresponding to one detection watermark. Watermarking Resisting to Translation, Rotation, and Scaling. Kutter, S. Bhattacharjee, T. Toward second generation watermarking schemes. Kutter, F. Jordan, F. Digital watermarking of color images using amplitude modulation.

Langelaar, R. Lagendijk, J. Removing spatial spread spectrum watermarks by non-linear filtering,. Lee, H. Robust image watermarking using local invariant features. Image adaptive watermarking using wavelet domain singular value decomposition. IEEE Trans. Circuits Syst. Video Technol. Li, B. Localized image watermarking in spatial domain resistant to geometric attacks, Int. AEU , 63 , pp. Lichtenauer, I. Setyawan, T. Kalker, R. Exhaustive geometrical search and the false positive watermark detection probability.

Licks, R. Geometric attacks on image watermarking systems. Lin, M. Wu, J. Bloom, I. Miller, Y. Rotation, scale, and translation- resilient public watermarking for images. Lin, R. Towards absolute invariants of images under translation, rotation and dilatation. Pattern Recognit. Lu, S. Huang, C. Sze, Liao H. Cocktail watermarking for digital image protection. Multimedia, 2 , pp. Lu, H.

Lu, F. Feature based watermarking using watermark template match. Math Comput. Luis, C. Pedro, P. Information Hiding, , pp. Macq, J. Dittmann, E. One the derivation of a chaotic encryption algorithm. Cryptologia, 8 , pp.

An information-theoretic view ofwatermark embedding-detection and geometric attacks,. Mikolajczyk, C. Proceedings of European Conference on Computer Vision, , pp. Interest point detection invariant to affine transformations, Institut National Polytechnique de Grenoble, ,. An affine invariant interest point detector, pp. Molina, A.

Higuera, J. Prieto, R. Airborne high-resolution digital imaging system. Journal of Applied Research and Technology, , pp. Moulin, J. Information-theoretic analysis of information hiding. IEEE Inform. Theory, preprint, 49 , pp. Pereira, T. Robust template matching for affine resistant image watermarks. Image Processing, 9 , pp. The JND model is usually used to describe the perception characteristics of human visual systems HVS Digital watermarking is a technique to put a secret message, which may be logo of a company, name of the creator, etc.

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