An FPP-resistant SVD-based image watermarking scheme based on chaotic control

Alshoura, Wafa’ Hamdan; Zainol, Zurinahni; Teh, Je Sen; Alawida, Moatsum

doi:10.1016/j.aej.2021.10.052

Cited by 26 publications

(15 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The NC metric has been used to determine the robustness of the presented color image watermarking method. The NC is calculated using the equation as given below: 24

N C = \frac{\sum_{i = 1}^{K} \sum_{j = 1}^{L} (W_{i, j}^{E} - W_{m}^{E}) (W_{i, j}^{O} - W_{m}^{O})}{\sqrt{(\sum_{i = 1}^{K} \sum_{j = 1}^{L} {(W_{i, j}^{E} - W_{m}^{E})}^{2}) (\sum_{i = 1}^{K} \sum_{j = 1}^{L} {(W_{i, j}^{O} - W_{m}^{O})}^{2})}},

where,

K \times L

is the grayscale watermark image size,

W_{i, j}^{E}

and

W_{i, j}^{O}

are pixels of the extracted and original watermarks,

W_{m}^{E}

and

W_{m}^{O}

are the mean values of the extracted and original watermarks, respectively 24 …”

Section: Resultsmentioning

confidence: 99%

“…Alshoura et al 24 Semi-blind High sensitivity to small changes in the secret key. Overcome false-positive problem issues.…”

Section: Type Pros Cosmentioning

confidence: 99%

“…) , (10) where, K × L is the grayscale watermark image size, W E i,j and W O i,j are pixels of the extracted and original watermarks, W E m and W O m are the mean values of the extracted and original watermarks, respectively. 24 To evaluate the robustness, the presented method is tested by various attacks including sharpening (SA), blurring (BA), average filtering (AF), resizing (RA), JPEG compression (JPEG), Poisson noise (PN), median filtering (MF), Gaussian white noise (GWN), speckle noise (SN), salt and pepper noise (SPN), and rotation attack (ROA). Details about attacks are shown in Table 3.…”

Section: Robustness Analysismentioning

confidence: 99%

“…Therefore, to increase watermarking capacity, some methods use the gray‐level watermark image instead of the binary watermark for color image watermarking. Alshoura et al 24 presented semi‐blind SVD based robust method using chaotic maps and IWT. In this work, grayscale watermark image was decomposed into eight bit‐planes, and then encrypted and re‐ordered using chaotic maps.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A blind robust color image watermarking method based on discrete wavelet transform and discrete cosine transform using grayscale watermark image

Gül

2022

Concurrency and Computation

View full text Add to dashboard Cite

With the rapid development of internet technology, digital images are easily accessed and tampered by unauthorized users. Therefore, copyright of color images has become an important challenge in nowadays. Robust color image watermarking methods have emerged to provide copyright. However, robust watermarking methods must satisfy the requirements such as robustness, imperceptibility, capacity, and security. Therefore, researchers are focused on methods using grayscale watermark instead of the binary watermark to increase capacity. Grayscale watermark based robust color image watermarking methods are mostly semi-blind and non-blind. However, these methods have limited utilization areas since the original image, original watermark, or side information is required. To address these drawbacks, we propose a blind robust color image watermarking method using grayscale watermark. In the proposed watermark embedding procedure, one-level discrete wavelet transform is performed on the Cb color component. Then, scrambled watermark pixels are hidden into coefficients of 4 × 4 discrete cosine transform (DCT) matrices of LL subband by using dividing-based new watermark embedding formula. In the watermark extracting procedure, watermark pixels are extracted from coefficients of DCT matrices by using dividing-based extracting formula. The performance is demonstrated against various attacks and experimental results indicate that the presented method ensures robustness while preserving imperceptibility.

show abstract

“…The NC metric has been used to determine the robustness of the presented color image watermarking method. The NC is calculated using the equation as given below: 24

N C = \frac{\sum_{i = 1}^{K} \sum_{j = 1}^{L} (W_{i, j}^{E} - W_{m}^{E}) (W_{i, j}^{O} - W_{m}^{O})}{\sqrt{(\sum_{i = 1}^{K} \sum_{j = 1}^{L} {(W_{i, j}^{E} - W_{m}^{E})}^{2}) (\sum_{i = 1}^{K} \sum_{j = 1}^{L} {(W_{i, j}^{O} - W_{m}^{O})}^{2})}},

where,

K \times L

is the grayscale watermark image size,

W_{i, j}^{E}

and

W_{i, j}^{O}

are pixels of the extracted and original watermarks,

W_{m}^{E}

and

W_{m}^{O}

are the mean values of the extracted and original watermarks, respectively 24 …”

Section: Resultsmentioning

confidence: 99%

“…Alshoura et al 24 Semi-blind High sensitivity to small changes in the secret key. Overcome false-positive problem issues.…”

Section: Type Pros Cosmentioning

confidence: 99%

Section: Robustness Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A blind robust color image watermarking method based on discrete wavelet transform and discrete cosine transform using grayscale watermark image

Gül

2022

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…The obvious diagonal traces are discovered in the extracted watermark under the attacks, which is due to the SVD used in the algorithms [19,20]. Moreover, the false positive problem (FPP) is easily found in the watermarking methods that used SVD [21][22][23]. Zhang et al [21] introduced generalized Arnold transform in the algorithm to solve the diagonal problem and FPP problem due to SVD.…”

Section: Introductionmentioning

confidence: 99%

A Watermarking Optimization Method Based on Matrix Decomposition and DWT for Multi-Size Images

Wang

2022

Electronics

View full text Add to dashboard Cite

Image watermarking is a key technology for copyright protection, and how to better balance the invisibility and robustness of algorithms is a challenge. To tackle this challenge, a watermarking optimization method based on matrix decomposition and discrete wavelet transform (DWT) for multi-size images is proposed. The DWT, Hessenberg matrix decomposition (HMD), singular value decomposition (SVD), particle swarm optimization (PSO), Arnold transform and logistic mapping are combined for the first time to achieve an image watermarking optimization algorithm. The multi-level decomposition of DWT is used to be adapted to multi-size host images, the Arnold transform, logistic mapping, HMD and SVD are used to enhance the security and robustness, and the PSO optimized scaling factor to balance invisibility and robustness. The simulation results of the proposed method show that the PSNRs are higher than 44.9 dB without attacks and the NCs are higher than 0.98 under various attacks. Compared with the existing works, the proposed method shows high robustness against various attacks, such as noise, filtering and JPEG compression and in particular, the NC values are at least 0.44% higher than that in noise attacks.

show abstract

A novel zero-watermarking algorithm based on robust statistical features for natural images

et al. 2022

View full text Add to dashboard Cite

In this paper, we develop a robust image zero-watermarking algorithm based on multiple circular statistical features. First of all, we detect stable feature points from the host image, and construct circular region partitions from the identified feature points, which contain the critical information of the host image. Second, the statistics and differences of circular region partitions are calculated, which contain both the local differences and the global information of the host image. Third, we apply discrete cosine transform (DCT) and singular value decomposition (SVD) in statistics and differences in order to construct the feature image. The stability of DCT and SVD further warrants the robustness of the algorithm. Moreover, Arnold transform is used to scramble the watermark image to enhance the security of the algorithm. Finally, we obtain the zero watermark by performing the exclusive-or (XOR) operation between the feature image and the scrambled watermark image, and the zero watermark is stored in the copyright authentication database for copyright authentication. Moreover, to combat geometric attacks, we develop a blind image correction algorithm without using the original image to accurately correct the attacked image. Numerous experiments and comparisons with the state-of-the-art (SOTA) watermarking algorithms confirm that the proposed algorithm affords good robustness against various attacks, such as filtering attacks, noise attacks, geometric attacks, and even a random combination of the above-stated attacks.

show abstract

An FPP-resistant SVD-based image watermarking scheme based on chaotic control

Cited by 26 publications

References 62 publications

A blind robust color image watermarking method based on discrete wavelet transform and discrete cosine transform using grayscale watermark image

A blind robust color image watermarking method based on discrete wavelet transform and discrete cosine transform using grayscale watermark image

A Watermarking Optimization Method Based on Matrix Decomposition and DWT for Multi-Size Images

A novel zero-watermarking algorithm based on robust statistical features for natural images

Contact Info

Product

Resources

About