Computationally Efficient Robust Color Image Watermarking Using Fast Walsh Hadamard Transform

Pullayikodi, Suja Kalarikkal; Tarhuni, Naser; Ahmed, Afaq; Shiginah, Fahad Bait

doi:10.3390/jimaging3040046

Cited by 10 publications

(4 citation statements)

References 8 publications

(8 reference statements)

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“…In such methods, the amplitude of certain transform coefficients is modulated according to the pseudorandomly generated watermark. Often, this is done in the discrete cosine transform (DCT) domain [5][6][7], although other transformations are commonly used as well [8,9]. For example, the dual-tree complex wavelet transform (DTCWT) method can be used to provide more robustness against geometric attacks [10][11][12].…”

Section: Forensic Watermarkingmentioning

confidence: 99%

“…To measure the robustness, the false-negative rate (FNR) is calculated. The FNR is defined in (8), and represents the fraction of false-negative (FN) detections, i.e., the fraction of watermarks that were not detected yet were present in the video under investigation. Additionally, the FNR is related to the true-positive rate (TPR) as defined in (9).…”

Section: Robustnessmentioning

confidence: 99%

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Fast Fallback Watermark Detection Using Perceptual Hashes

et al. 2021

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Forensic watermarking is often used to enable the tracing of digital pirates that leak copyright-protected videos. However, existing watermarking methods have a limited robustness and may be vulnerable to targeted attacks. Our previous work proposed a fallback detection method that uses secondary watermarks rather than the primary watermarks embedded by existing methods. However, the previously proposed fallback method is slow and requires access to all watermarked videos. This paper proposes to make the fallback watermark detection method faster using perceptual hashes instead of uncompressed secondary watermark signals. These perceptual hashes can be calculated prior to detection, such that the actual detection process is sped up with a factor of approximately 26,000 to 92,000. In this way, the proposed method tackles the main criticism about practical usability of the slow fallback method. The fast detection comes at the cost of a modest decrease in robustness, although the fast fallback detection method can still outperform the existing primary watermark method. In conclusion, the proposed method enables fast and more robust detection of watermarks that were embedded by existing watermarking methods.

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Section: Forensic Watermarkingmentioning

confidence: 99%

Section: Robustnessmentioning

confidence: 99%

Fast Fallback Watermark Detection Using Perceptual Hashes

et al. 2021

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“…The most common transforms used for watermark insertion are discrete cosine transform (DCT) [ 4 , 5 , 6 , 7 ], discrete Fourier transform (DFT) [ 8 , 9 ], discrete wavelet transforms (DWT) [ 10 , 11 ], and Walsh–Hadamard transform [ 12 ]. In addition, transform-based methods can be used jointly with other techniques, such as, e.g., discrete fractional random transform (DFRNT) [ 3 ] or singular value decomposition (SVD) [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of New Orthogonal Transforms for Digital Watermarking

Bogacki

Dziech

2022

Sensors

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The paper focuses on the application of new orthogonal transforms in digital watermarking. Novel types of transforms and their characteristics are presented. Potential methods for watermark embedding and recovery are also proposed. They assume embedding hidden information in the transform domains using the luminance channel of the original image. Image spectra are obtained by dividing the original image into smaller blocks that then are further processed by performing the forward transform operation. A watermark is embedded by modifying the spectral coefficients with relatively low values. Since there are various types of transforms, the latter process is realized in an adaptive manner. The proposed solutions were evaluated by measuring the level of visual distortion with respect to the total size of the inserted data. Additionally, the bit error rate (BER) in the recovery phase is also analyzed. The elaborated methods seem to be useful for applications in digital signal and image processing where high imperceptibility and low BER are of great importance. New orthogonal transforms were proved to be useful in watermarking tasks, and in some cases, they can even outperform the classic DCT approach.

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“…Indeed, the forward and inverse transforms have the same structure, only differing in the constant coefficient. The proposed transforms could be effectively applied in such areas of signal and image processing as watermarking technology [10][11][12], steganography, intelligent monitoring and others [13][14][15][16]. The general form of this transform enables the possibility of selecting optimal parameters for specific tasks, implying there are potentially other applications.…”

Section: Introductionmentioning

confidence: 99%

New Orthogonal Transforms for Signal and Image Processing

Dziech

2021

Applied Sciences

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In the paper, orthogonal transforms based on proposed symmetric, orthogonal matrices are created. These transforms can be considered as generalized Walsh–Hadamard Transforms. The simplicity of calculating the forward and inverse transforms is one of the important features of the presented approach. The conditions for creating symmetric, orthogonal matrices are defined. It is shown that for the selection of the elements of an orthogonal matrix that meets the given conditions, it is necessary to select only a limited number of elements. The general form of the orthogonal, symmetric matrix having an exponential form is also presented. Orthogonal basis functions based on the created matrices can be used for orthogonal expansion leading to signal approximation. An exponential form of orthogonal, sparse matrices with variable parameters is also created. Various versions of orthogonal transforms related to the created full and sparse matrices are proposed. Fast computation of the presented transforms in comparison to fast algorithms of selected orthogonal transforms is discussed. Possible applications for signal approximation and examples of image spectrum in the considered transform domains are presented.

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Computationally Efficient Robust Color Image Watermarking Using Fast Walsh Hadamard Transform

Cited by 10 publications

References 8 publications

Fast Fallback Watermark Detection Using Perceptual Hashes

Fast Fallback Watermark Detection Using Perceptual Hashes

Analysis of New Orthogonal Transforms for Digital Watermarking

New Orthogonal Transforms for Signal and Image Processing

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