A Bayesian Approach to Affine Transformation Resistant Image and Video Watermarking

Deguillaume, Frédéric; Ruanaidh, Joseph Ó; Pun, Thierry

doi:10.1007/10719724_19

Cited by 30 publications

(18 citation statements)

References 12 publications

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“…It is a well-known fact [18] that many existing image watermarking algorithms are vulnerable to this kind of attacks. There have been some efforts and progress in addressing this issue [12][13][14][15][19][20][21][22][23][24][25][26][27][28][29]. Among various techniques that have appeared in the literature, we are most interested in the invariant watermarking approach, which is based on the invariance property of some image features.…”

Section: Introductionmentioning

confidence: 99%

Circularly orthogonal moments for geometrically robust image watermarking

Xin

Liao

Pawlak

2007

Pattern Recognition

151

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Section: Introductionmentioning

confidence: 99%

Circularly orthogonal moments for geometrically robust image watermarking

Xin

Liao

Pawlak

2007

Pattern Recognition

151

View full text Add to dashboard Cite

“…As explained in the introduction, some current attacks operate by disrupting synchronization. Such attacks do not actually remove or destroy the watermark, so a more sophisticated receiver should be able to resynchronize [24,17,7,6,18]. Hence, we assume synchronization throughout this paper.…”

Section: Watermark Receptionmentioning

confidence: 99%

Analysis of digital watermarks subjected to optimum linear filtering and additive noise

Eggers

Girod

2001

Signal Processing

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Using a theoretical approach based on random processes, signal processing, and information theory, we study the performance of digital watermarks subjected to an attack consisting of linear shift-invariant filtering and additive colored Gaussian noise. Watermarking is viewed as communication over a hostile channel, where the attack takes place. The attacker attempts to minimize the channel capacity under a constraint on the attack distortion (distortion of the attacked signal), and the owner attempts to maximize the capacity under a constraint on the embedding distortion (distortion of the watermarked signal). The distortion measure is frequency-weighted mean-squared error (MSE). In a conventional additive-noise channel, communication is most difficult when the noise is white and Gaussian, so we first investigate an effective white-noise attack based on this principle. We then consider the problem of resisting this attack and show that capacity is maximized when a power-spectrum condition (PSC) is fulfilled. The PSC states that the power spectrum of the watermark should be directly proportional to that of the original signal. However, unlike a conventional channel, the hostile attack channel adapts to the watermark, not vice versa. Hence, the effective white-noise attack is suboptimal. We derive the optimum attack, which minimizes the channel capacity for a given attack distortion. The attack can be roughly characterized by a rule-of-thumb: At low attack distortions, it adds noise, and at high attack distortions, it discards frequency components. Against the optimum attack, the PSC does not maximize capacity at all attack distortions. Also, there is no unique watermark power spectrum that maximizes capacity over the entire range of attack distortions. To find the watermark power spectrum that maximizes capacity against the optimum attack, we apply iterative numerical methods, which alternately adjust the watermark power spectrum and re-optimize the parameters of the optimum attack. Experiments using ordinary MSE distortion lead to a rule-of-thumb: White watermarks perform nearly optimally at low attack distortions, while PSC-compliant watermarks perform nearly optimally at high attack distortions. The effect of interference from the original signal in suboptimal blind watermarking schemes is also considered; experiments examine its influence on the optimized watermark power spectra and the potential increase in capacity when it can be partially suppressed. Additional experiments demonstrate the importance of memory, and compare the optimum attack with suboptimal attack models. Finally, the rule-of-thumb for the defense is extended to the case of frequency-weighted MSE as a distortion measure.

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“…In order to reduce the performance degradation under certain attacks such as geometric attacks and to take advantage of the properties of certain transform domain, the message embedding can be performed in different domains such as the discrete cosine transform (DCT) domain [27], the discrete Fourier transform (DFT) domain [28][29][30][31], and the discrete wavelet transform (DWT) domain [32,33].…”

Section: Introductionmentioning

confidence: 99%

Efficient blind decoders for additive spread spectrum embedding based data hiding

Valizadeh

Wang

2012

EURASIP J. Adv. Signal Process.

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This article investigates efficient blind watermark decoding approaches for hidden messages embedded into host images, within the framework of additive spread spectrum (SS) embedding based for data hiding. We study SS embedding in both the discrete cosine transform and the discrete Fourier transform (DFT) domains. The contributions of this article are multiple-fold: first, we show that the conventional SS scheme could not be applied directly into the magnitudes of the DFT, and thus we present a modified SS scheme and the optimal maximum likelihood (ML) decoder based on the Weibull distribution is derived. Secondly, we investigate the improved spread spectrum (ISS) embedding, an improved technique of the traditional additive SS, and propose the modified ISS scheme for information hiding in the magnitudes of the DFT coefficients and the optimal ML decoders for ISS embedding are derived. We also provide thorough theoretical error probability analysis for the aforementioned decoders. Thirdly, sub-optimal decoders, including local optimum decoder (LOD), generalized maximum likelihood (GML) decoder, and linear minimum mean square error (LMMSE) decoder, are investigated to reduce the required prior information at the receiver side, and their theoretical decoding performances are derived. Based on decoding performances and the required prior information for decoding, we discuss the preferred host domain and the preferred decoder for additive SS-based data hiding under different situations. Extensive simulations are conducted to illustrate the decoding performances of the presented decoders.

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A Bayesian Approach to Affine Transformation Resistant Image and Video Watermarking

Cited by 30 publications

References 12 publications

Circularly orthogonal moments for geometrically robust image watermarking

Circularly orthogonal moments for geometrically robust image watermarking

Analysis of digital watermarks subjected to optimum linear filtering and additive noise

Efficient blind decoders for additive spread spectrum embedding based data hiding

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