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A new image data-hiding technique is proposed. The proposed approach modifies blocks of the image after projecting them onto certain directions. By quantizing the projected blocks to even and odd values, one can represent the hidden information properly. The proposed algorithm performs the modification progressively to ensure successful data extrac...
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... and are arbitrary eigenvectors in and , respectively. The motivation for using the angle as a measure for robustness is that it gives us a sense of how much the space has been rotated due to the performed attacks. This is acceptable since a rotated space means different projection values and, hence, more errors in the embedding results. Figs. 18 – 20 show for different values for JPEG coded with different Qs, scaled and rotated images. It is clear that the fi rst eigenvector is highly robust to the performed attacks, this justi- fi es the use of the fi rst eigenvector as the projection space in the proposed embedding algorithm. Unfortunately, the eigenspace is not robust to blurring attack, and, hence, the embedding algorithm does not survive blurring attacks. The robustness of the proposed embedding algorithm to AWGN, JPEG coding, combined scaling, and rotation has been tested. Fig. 21(a) and (b) illustrates the percentage BER versus for different PSNR for f16 and pot images, respectively. As can be seen from the fi gures, the BER decreases with the increase of and PSNR, as expected. Fig. 22(a) and (b) illustrates the performance of the embedding algorithm to JPEG coding for different Q factors for the F16 and Mandrill images, respectively. Robustness to combined scaling and rotation attacks is illustrated by Fig. 23(a) and (b) for Cameraman and Lena images with and , respectively. The fi gures show the percentage BER as a function of different scales and rotation angles after regaining synchronization. As it is clear from the fi gures, the BER increases dramatically with downscaling the image. This can be understood from the inherent data loss accompanied with the downsampling process. On the other hand, enlarging the image has little effect on the error due to the redundancy introduced by the interpolation process. The performance of the algorithm as a function of angle and scaling factor estimation error is illustrated in Fig. 24. It is clear from the fi gure that the algorithm is sensitive to estimation error which can be understood from the desyn- chronization effect produced by the estimation error. Hence, the fi ne tuning step introduced in Section IV-B is important to maintain low BER. Finally, Fig. 25 shows the contour plot of the 2-D autocorrelation function of the original pot image and the corresponding watermark embedded with . It is clear that the watermark power spectrum 1 follows that of the original image, i.e., the power spectrum condition is satis fi ed [41]. VI. C ONCLUSION A new data-hiding technique has been presented in this paper. Data is embedded by quantizing the projection of the 8 8 blocks onto the eigensubspaces extracted from the image. The proposed data embedding algorithm assumes blind detection where no overhead is required for detection. Two techniques are proposed for synchronization recovery, exhaustive search, and scaling-rotation parameters estimation. The exhaustive search technique uses preembedded training sequence for locking to the right scale and orientation. On the other hand, scaling factors and rotation angles are estimated with the aid of wavelet maxima. Performance analysis and robustness tests were also presented. A CKNOWLEDGMENT The authors would like to thank Dr. G. Sharma and the anony- mous reviewers for their help in improving the quality of this ...
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... 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. ...
Over the past several decades, digital information science has emerged to seek answers to the question: can any technique ensure tamper-resistance and protect the copyright of digital contents by storing, transmitting and processing information encoded in systems where digital content can easily be disseminated through communication channels? Today it is understood that the answer is yes. This paper reviews the theoretical analysis and performance investigation of representative watermarking systems in transform domains and geometric invariant regions. Digital watermarking is a technology of embedding watermark with intellectual property rights into images, videos, audios, and other multimedia data by a certain algorithm. The basic characteristics of digital watermark are imperceptibility, capacity, robustness and false positive of watermarking algorithm and security of the hiding place. 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.
... Different types of image features, e.g., corners [3], wavelet maxima points [4], have been extensively used in the last decade in order to obtain robust watermarking-based copyright protection systems. Corners are visually distinguishable and well localized compared to other image features. ...
... Corners are visually distinguishable and well localized compared to other image features. The wavelet maxima-based watermarking system in [4] could survive only on small geometric distortions, e.g., 2 • rotation. The reason is that the wavelet features are highly sensitive to geometric operations. ...
There are many applications, such as image copyright protection, where transformed images of a given test image need to be identified. The solution to this identification problem consists of two main stages. In stage one, certain representative features, such as corners, are detected in all images. In stage two, the representative features of the test image and the stored images are compared to identify the transformed images for the test image. Curvature scale-space (CSS) corner detectors look for curvature maxima or inflection points on planar curves. However, the arc-length used to parameterize the planar curves by the existing CSS detectors is not invariant to geometric transformations such as scaling. As a solution to stage one, this paper presents an improved CSS corner detector using the affine-length parameterization which is relatively invariant to affine transformations. We then present an improved corner matching technique as a solution to the stage two. Finally, we apply the proposed corner detection and matching techniques to identify the transformed images for a given image and report the promising results.
... There are different types of image features discussed in the literature, for example, wavelet-maxima points [2,101,157], moment invariants [62], corners [118] and interest-points [67]. Among them corners are the most visually significant featurepoints. ...
... • Robust Features: In contrast to other feature-points like wavelet-maxima points [2] and interest-points [67], corners are visually significant and more robust. The wavelet-maxima points cannot survive even in moderate geometric transformations [2] and it was shown that corners are more robust than interest-points [71]. ...
... • Robust Features: In contrast to other feature-points like wavelet-maxima points [2] and interest-points [67], corners are visually significant and more robust. The wavelet-maxima points cannot survive even in moderate geometric transformations [2] and it was shown that corners are more robust than interest-points [71]. ...
Corners are visually distinguishable, well localized, and more robust than other image
feature-points like wavelet-maxima points. The contour-based multi-scale corner detectors,
commonly known as curvature scale-space (CSS) detectors, first obtain planar
curves using some edge detector and then search for the curvature-maxima points
along those curves in the scale-space. The existing CSS-based detectors suffer from
two main problems. First, their curvature estimation technique considers a very small
neighborhood which makes the corner detection technique sensitive to the local variations
and the noise on the curve. Second, they require appropriate curve smoothingscale
selection which is difficult in practice. Any successful application of a corner
detector requires a sophisticated matching technique. Existing corner matching techniques
are computationally intensive and may not be able to obtain all the repeated
corners between different versions (transformed and signal processed) of the same
image.
This thesis first presents an improved contour-based multi-scale corner detector
that parameterizes the extracted curves using the affine-length. This improved detector
shows better performance than the existing CSS detectors in geometric transformed
images. Then a new multi-scale corner detector is presented that uses the
chord-to-point distance accumulation technique of discrete curvature estimation. The
proposed new detector considers a large neighborhood and does not require the appropriate
smoothing-scale selection, and thus overcomes the main problems associated
with the existing CSS detectors. Finally, a new geometric point matching technique
is proposed that obtains all the repeated corners within the allowed localization
error.
The proposed corner detectors and matching technique in transformed image identification
and copyright protection.
... Geometric transformations can be decomposed into two classes: global transformations such as rotation, scaling, and translation (RST) and local transformations like local bending attacks. A lot of schemes [1][2][3][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] have been proposed to combat both types of transformations; nonetheless, the problem of resisting geometric attacks has been unsolved yet because of their high computational complexity, implementation difficulties, and poor performance. In addition, many of the existing schemes are vulnerable to rotation-scale and cropping attacks. ...
... However, geometric transformations of the watermarked content create synchronization problem in the watermark detection or extraction phase. There are many synchronizing schemes to combat geometric attacks in the literature [1][2][3][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. They may be divided into following seven classes. ...
... As the image content represents an invariant reference to geometrical transformations, these schemes locate the mark by linking with image semantics. For feature extraction they used Harris corner and edge detector [9,[19][20], Mexican Hat wavelet scale interaction model [13,15], wavelet maxima [14], scaleinvariant feature transform [16], image segmentation [17], and scale-space representation of the image [18] [20]. However, their effectiveness was limited. ...
The performance of existing copyright protection schemes is questionable due to their vulnerability to geometric transformations. Though a few of them can resist global geometric transformations like rotation and scaling attacks, most of them are vulnerable to rotation-scale and cropping attacks. This paper presents a novel geometric distortion correction scheme robust to global geometric transformations. It restores an attacked image to its approximate original by reversing the attack using the invariant centroid and geometric moments of the image. Experimental results show the effectiveness of the proposed scheme
The data transmission on network channel is of tremendous increases from the past few decades. Watermarking is a process to add watermark as a digital signal, label or tag into a cover media. The primary requirements of multimedia watermarking are robustness and embedding capability. The robustness is defined as the strength of an algorithm to repel the noise. However, it is challenging to achieve both at the same time. The numerous characteristics of watermarking are very imperative in the multimedia watermarking system. The researchers are using watermarking schemes in various applications such as military, digital forensics, medical and so on. Attacks of these watermarking harm or uncover the secret information carried in the watermark. Potential researchers have been presented various techniques for balancing or improving these concerns. In this chapter, the recent multimedia watermarking techniques are reviewed on the basis of robustness and embedding capability. Further, this article introduces the characteristics, applications and attacks on multimedia watermarking techniques.
How to resist geometric attacks is currently the focus and difficulty in video watermarking fields. This paper presents a video dual watermarking method which could effectively resist geometric attacks. The method mines a geometric deformation invariant, namely the low-dimensional manifold of video, and theoretically derives and experimentally demonstrates geometric invariance. First of all, the method generates zero-watermark or dynamic semantics watermark online according to low-dimensional manifolds of different video shots. In order to balance the robustness and transparency, the method embeds watermark in the IF DCT coefficients of AVS predicted residuals with large energy. This paper studies deeply the three-dimensional space-time characteristics of video, effectively quantifies and characterizes video motion information by low-dimensional manifold of video, establishes the human dynamic masking model including movement features, brightness features and texture features, so as to adaptively control watermark embedding strength. Experiments and analysis show that this method can effectively resist center cutting, irregular cutting, row cutting, rotation, scaling, translation and other high intensity geometric attacks and combined attacks, such as rotation and corner cutting, center cutting and rotation, etc. It also has strong robustness to the conventional video signal processing and various video attacks.
Digital watermarking technique is a leading international research field in recent years. Though watermarking algorithms based on scalar wavelet transforms have become a hot-discussed research aspect and fruitful achievements have been obtained. but the ones based on multi-wavelet transforms have appeared few. Multi-wavelet has symmetric, orthogonality and compact support at the same time. They are important properties in image processing. In the paper, watermarking system in multi-wavelet domain has been studied, and a multi-wavelet transform based JND digital watermarking algorithm has been proposed. By calculating the textutre measures of the multi-wavelet coefficients in the low frequency, the JND calculation model has been improved. The experiment result shows that by using JND calculating model based on texture measures, the robustness of the JND threshold is improved, and the watermark embeded position can be located exactly, at the same time the digital watermark extraction result is significantly improved.
JND threshold is usually used to control the embedding location and intensity in image watermarking system, and to determine the extraction location in blind algorithm as well. A novel JND computation method based on the low frequency coefficients of wavelet domain and texture measures is present to enhance the robustness of JND threshold. Most of the embedded watermarks can be effectively located even when the image is largely altered, thus it can improve efficaciously the detection result in blind extraction. Besides, a novel blind detection algorithm called matching detection based on statistical characteristics is given. Matching detection enhances detecting responses and obtains high credibility considering the probability of false alarm.
In the digital watermarking technology based on wavelet transforms, it is of practical significance to improve the robustness of the JND (just noticeable difference) model and to control the probability of false alarm when extracting the watermarks from the watermarking systems. In the paper, a new watermark embedding algorithm has been studied and several experiments have been done as follows: a wavelet-based blind watermark detecting algorithm is proposed, which can determine the alarm threshold based on statistical characteristics, thereby quantitatively controlling the probability of false alarm; the JND model is improved, which enhances the robustness of JND model; and most of the embedded watermark can be effectively located even when the image is significantly modified. The algorithm proposed here is especially beneficial to blind extractions.
It is well known that symbol timing offsets larger than the cyclic prefix between transmitter and receiver stations destroy the orthogonality among OFDM subcarriers inducing interblock interference by coupling subsequent OFDM symbols. In conjunction with MIMO transmission over frequency selective channels, this effect on top of multi-user interference strongly degrades performance. In this paper we analyze the timing constraints in cellular MIMO OFDM networks that necessarily occur due to time-of-arrival differences of signals from different locations. We investigate a simple hexagonal model, where three users transmit their data on the same time-frequency resource to three cooperating base stations. Based on a detailed analytical derivation of the transmission model we present results for the post detection SINR in systems with symmetric and uniform user distribution within one cooperative cell.
