A DWT-SVD based adaptive color multi-watermarking scheme for copyright protection using AMEF and PSO-GWO

Shen, Yuxin; Tang, Chen; Xu, Min; Chen, Mingming; Lei, Zhenkun

doi:10.1016/j.eswa.2020.114414

Cited by 51 publications

(26 citation statements)

References 62 publications

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“…The ABC algorithm is used to determine the optimal channel distortion parameters ( α, ∆, and δ) by finding the best match between the embedded reference message R and the extracted one from y H R using Eq. (8). These parameters will be used to extract P from y H P .…”

Section: Reframed Watermark Extraction (Rwe) Schemementioning

confidence: 99%

“…However, the optimization of one objective solely limits the scheme's performance. To overcome this limi-tation, the concept of weighting factors was introduced, where each watermark characteristics (imperceptibility, HC, and robustness) are weighted according to the application requirements, then summed to define one objective function [5][6][7][8][9][10] . For instance, Shen et al [8] defined the objective function using correlation coefficient to represent both the imperceptibility and the robustness; in the former between the original image and the watermaked one, and in the latter between the inserted watermark (image) and the retrieved one.…”

Section: Introductionmentioning

confidence: 99%

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A Reframed Watermark Extraction Approach Using the ABC Algorithm

Kricha

Sakly

2021

Chinese J of Electronics

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The fast development and the rapid spread of information technology have raised the issue of digitalimage copyright protection, which was mostly addressed through robust watermarking. To ensure the survival of the watermark after attacks, most works have been making use of an additional step at the embedding phase, and by so making the scheme unsuitable for real-time implementation. However, to be effective and secure, it is recommended to combine the watermarking algorithm and the capture sensor in one device. In this paper, we brought the extra stage to the detection side. We firstly studied the effect of some signal processing operations on a watermarked image, then we proposed a general model for watermark extraction whose parameters were determined using the artificial bee colony. The efficacy of the proposed method was validated by comparing its robustness with two state-of-art schemes focusing on the watermark extraction.

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Section: Reframed Watermark Extraction (Rwe) Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Reframed Watermark Extraction Approach Using the ABC Algorithm

Kricha

Sakly

2021

Chinese J of Electronics

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“…A type of classification of digital watermarking is generated in accordance with the differences of watermark embedding domains, namely spatial‐domain watermarking 15,16 and frequency‐domain watermarking 17–27 . For the first kind of watermarking, the purpose of embedding watermark is attained through altering the pixel value of carrier images directly using certain rules.…”

Section: Introductionmentioning

confidence: 99%

“…A type of classification of digital watermarking is generated in accordance with the differences of watermark embedding domains, namely spatial-domain watermarking 15,16 and frequencydomain watermarking. [17][18][19][20][21][22][23][24][25][26][27] For the first kind of watermarking, the purpose of embedding watermark is attained through altering the pixel value of carrier images directly using certain rules. It has the specialties of low algorithm complexity, easy implementation, and large embedding payload, which is appropriate for the occasion with high performance requirements of time, however the robustness is limited.…”

Section: Introductionmentioning

confidence: 99%

“…Its robustness has been greatly improved compared to spatial-domain watermarking, nevertheless the computational complexity is usually relatively high, and the embedding capacity is relatively low. Commonly used transforms in this field include discrete Fourier transform (DFT), 17,18 discrete Cosine transform (DCT), 19,20 discrete Wavelet transform (DWT), 21,22 matrix decomposition 23,24 and other transforms, 25,26 and so on. For instance, Fares et al 17 applied two proposed variants to label the coefficients acquired from three types of Fourier transform to compare, which some experiment statistics display that this approach has better robustness against filtering and other attacks.…”

Section: Introductionmentioning

confidence: 99%

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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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An efficient image steganography approach based on QR factorization and singular value decomposition in non‐subsampled contourlet transform domain

Yasmeen

Uddin

2022

Security and Privacy

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As the amount of information communicated through the virtual world grows dramatically day by day, data security becomes a significant concern while communicating over the internet. Steganography can play an integral part in safeguarding the data from unauthorized users through a hiding mechanism. This article describes a three-step steganographic algorithm. This algorithm applied QR factorization and singular value decomposition (SVD) in the non-subsampled contourlet transform (NSCT) domain. First, this algorithm scrambles the secret image using Arnold transforms, and then NSCT decomposes the carrier and the scrambled hidden image into coefficient sub-bands. Second, the QR factorization and SVD are used on the specific coefficients of carrier and scrambled secret images, respectively. Finally, the modified secret image inserts into the carrier image for communication. The reverse mechanism is applied to discover the hidden message at the receiving end. The methodology gives superior imperceptibility as well as robustness. Furthermore, the anticipated strategy is compared with current methods in terms of effectiveness.

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A DWT-SVD based adaptive color multi-watermarking scheme for copyright protection using AMEF and PSO-GWO

Cited by 51 publications

References 62 publications

A Reframed Watermark Extraction Approach Using the ABC Algorithm

A Reframed Watermark Extraction Approach Using the ABC Algorithm

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

An efficient image steganography approach based on QR factorization and singular value decomposition in non‐subsampled contourlet transform domain

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