A Channel-Dependent Statistical Watermark Detector for Color Images

Amini, Marzieh; Sadreazami, Hamidreza; Ahmad, M. Omair; Swamy, M.N.S.

doi:10.1109/tmm.2018.2851447

Cited by 51 publications

(18 citation statements)

References 20 publications

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“…In Table 6, the average AUROC values of multiple test images are obtained under Gaussian filtering, cropping, rotation, scaling and gamma correction attacks. As can be observed from the table, although the performance of the detector in this paper is similar to that of HMM-based detector [24] under strong gamma correction and cropping attacks, on the whole, the proposed detector provides larger AUROC values than other detectors under both conventional attacks and geometric attacks. To clearly prove the robustness of the suggested algorithm, Fig.…”

Section: Auroc Values Under Various Attacksmentioning

confidence: 62%

“…As shown in this table, the proposed watermark scheme provides lower time complexity, larger watermark capacity and stronger imperceptibility. Sadreazami's NIG [5], Amini's CHMM [24], Amirmazlaghani's WT-GARCH [37], and Amini's WHMM [7] based methods. We selected these eight methods based on their similarities to the proposed approach, and based on the presence of sufficient algorithm descriptions (including implementation details and parameter settings etc.)…”

Section: Capacity and Timementioning

confidence: 99%

“…12, we can see that the suggested LO detector under JPEG compression attacks provides more robust properties than that of other detectors. Especially compared with the optimal algorithm [24] in existing detectors, the proposed detector is more likely to detect watermarks under strong attack condition with QF =5. Fig.…”

Section: Auroc Values Under Various Attacksmentioning

confidence: 99%

See 2 more Smart Citations

A New Statistical Image Watermark Detector in RHFMs Domain using Beta Exponential Distribution

Niu

Tian

et al. 2021

Preprint

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The detection of watermarks can be achieved by statistical approaches. How to select robust modeling object, appropriate statistical model, and decision rules is one of the major issues in statistical image watermark detection. In this paper, we propose a new image watermark detector in robust fast radial harmonic Fourier moments (FRHFMs) magnitudes domain, wherein the Beta exponential distribution model and locally most powerful (LMP) decision rule are used. We first investigate the statistical modeling of the robust FRHFMs magnitudes by the Beta exponential distribution. It is shown that the Beta exponential distribution model fits the empirical data more accurately than the formerly employed statistical distributions, such as the Cauchy, Weibull, BKF and Exponential, do. Motivated by the statistical modeling results, we design a blind image watermark detector in FRHFMs magnitudes domain by using Beta exponential distribution and LMP test. Also, we utilize the Beta-exponential model to derive the closed-form expressions for the watermark detector. We provide comparative experimental results to alternative approaches to demonstrate the advantages of the proposed image watermark detector.

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Section: Auroc Values Under Various Attacksmentioning

confidence: 62%

Section: Capacity and Timementioning

confidence: 99%

See 1 more Smart Citation

A New Statistical Image Watermark Detector in RHFMs Domain using Beta Exponential Distribution

Niu

Tian

et al. 2021

Preprint

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show abstract

“…The operation significantly improves robustness and resistance to channel interference. In the case where the size of the embedded key is much smaller than the maximum hidden capacity of the channel code [30], the concealment of the key is greatly enhanced.…”

Section: Proposed Schemementioning

confidence: 99%

Reversible data hiding in encrypted images for coding channel based on adaptive steganography

Chen

Wang

et al. 2020

IET image process

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In this study, a novel reversible data hiding (RDH) in encrypted domain scheme for coding channel based on slidingblock segmentation and adaptive steganography is proposed. The proposed scheme enriches the residual information with as little additional encryption information as possible to improve the testing error rate of a steganalyser by sliding-block segmentation with bit stream encryption. The specific encryption process effectively weakens the correlation between the adjacent pixels and minimises the size of key stream bits. The encryption key can be further embedded in the channel code stream before transmitted in the channel. Experimental analysis shows that the image encrypted by the proposed RDH scheme can achieve a peak-signal-to-noise ratio of >50 dB, as the payload is 0.5 bits per pixel (bpp). In terms of security performance, compared with the state-of-the-art methods, their method has a higher testing error rate when the steganalyser is utilised. Even if the payload is 0.5 bpp, the testing error rate is >0.25.

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“…Currently, there exist two extraction ways in watermarking, that is, nonblind extraction 27 and blind extraction. 28,29 The former needs the assistance of original carrier or watermark during entire operation procedure. It is hard to obtain the original data in the extraction process in most cases yet.…”

Section: Introductionmentioning

confidence: 99%

A spatial domain‐based color image blind watermarking scheme integrating multilevel discrete Hartley transform

Zhang

2021

Int J Intell Syst

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In this paper, a spatial domain‐based blind watermarking scheme of color images integrating multilevel discrete Hartley transform (DHT) is proposed to protect color digital images' copyright under the current 5G network environment. On the basis of the unique spatial computing property of the maximum energy coefficient of DHT and the energy aggregation principle of multilevel image transform, the color watermark image scrambled by Affine transform is directly hidden into color carrier image by quantitative techniques in the spatial domain, rather than the complex DHT domain. The specific performance of the scheme in various aspects is as follows: (1) the average value of the peak signal‐to‐noise ratio is higher than 40 dB; (2) the average value of structural similarity index metric remains above 0.9700; (3) the average value of normalized cross‐correlation under no attack is 1.0000; (4) the average value of normalized cross‐correlation. under attack is above 0.9600; (5) the total execution time is 1.1856 s; (6) the maximum embedding capacity is 0.0625 bpp; and (7) the entire key space is greater than 2432. Multiple simulation results demonstrate that the proposed scheme is not merely imperceptible and robust, but also secure and efficient, which can protect the digital copyright with effect.

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A Channel-Dependent Statistical Watermark Detector for Color Images

Cited by 51 publications

References 20 publications

A New Statistical Image Watermark Detector in RHFMs Domain using Beta Exponential Distribution

A New Statistical Image Watermark Detector in RHFMs Domain using Beta Exponential Distribution

Reversible data hiding in encrypted images for coding channel based on adaptive steganography

A spatial domain‐based color image blind watermarking scheme integrating multilevel discrete Hartley transform

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