An Optimized Digital Watermarking Scheme Based on Invariant DC Coefficients in Spatial Domain

Ali, Musrrat; Ahn, Chang Wook; Pant, Millie; Kumar, Sanoj; Singh, Manoj K.; Saini, Deepika

doi:10.3390/electronics9091428

Cited by 17 publications

(16 citation statements)

References 36 publications

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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%

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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%

“…Finally, using the obtained z-score and threshold, a decision d i of watermark presence or absence can be made using (6). In other words, a watermark's presence is detected when the corresponding z-score is larger than this threshold.…”

Section: Fast Fallback Detection Using Perceptual Hashesmentioning

confidence: 99%

Fast Fallback Watermark Detection Using Perceptual Hashes

et al. 2021

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“…Watermarking can be executed in a spatial domain [4,13,23,28,29] or a transform domain [3,[5][6][7][8][9][10][11][12]14,15,18,19,21,22,[24][25][26][27][30][31][32][33][34][35]. The spatial domain watermarking has high efficiency by modifying the pixels of the host images or frames directly to embed the watermark.…”

Section: Related Workmentioning

confidence: 99%

“…The spatial domain watermarking has high efficiency by modifying the pixels of the host images or frames directly to embed the watermark. In comparison, the transform domain watermarking modifies the coefficients obtained by transformation, such as the Discrete Cosine Transform (DCT) [8][9][10]18,19,21,22,24,26,30,31], Discrete Wavelet Transform (DWT) [7,11,12,14,[25][26][27]32,33], Singular Value Decomposition (SVD) [6,12,25,26], Discrete Multiwavelet Transformation (DMT) [3], Contourlet Transform [6], Dual-Tree Complex Wavelet Transform (DT CWT) [5,15,34], and so on. They possess better imperceptibility and robustness, but their computational complexity is higher than that of the spatial domain watermarking.…”

Section: Related Workmentioning

confidence: 99%

“…After determining the embedding domain, we should modify or analyze its coefficients to embed and extract the watermark. The quantization methods [7][8][9][10][16][17][18][19][20][21] are typical watermark embedding and extracting methods. It divides the reference axis into multiple index intervals, and each index interval corresponds to one component (0 or 1) of the watermark.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Video Watermarking against Scaling Attacks Based on Quantization Index Modulation

Huang

Guan

et al. 2021

Electronics

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Video watermarking plays a vital role in protecting the video copyright. The quantization-based methods are widely used in the existing watermarking algorithms, owing to their low computational complexity and completely blind extraction. However, most of them work poorly in resisting scaling attacks, by which the quantization value may fall outside the original quantization interval. For addressing this issue, an adaptive quantization index modulation method is proposed. The property that is associated with the ratio of the DC coefficient before and after scaling the video resolution motivates us to select the DC coefficient as the quantization value and set the size of the quantization interval by the video resolution to maintain the synchronization between them before and after scaling. Moreover, a strategy taking advantage of the high decoding reliability of the QRCode is proposed to terminate the extraction in advance, and both the embedding and the extracting process are performed in the spatial domain, which all contribute to further enhance the execution efficiency. The experimental results show that our algorithm outperforms the state-of-the-art method in terms of imperceptibility, robustness, and computational cost.

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