LWT- QR decomposition based robust and efficient image watermarking scheme using Lagrangian SVR

Mehta, Rajesh; Rajpal, Navin; Vishwakarma, Virendra P.

doi:10.1007/s11042-015-3084-5

Cited by 40 publications

(19 citation statements)

References 22 publications

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“…Geometric features of an image can be extracted by using matrix decomposition method and the robustness is more against geometric attacks. Consequently, he combination of DWT and matrix decomposition are applied in watermarking techniques takes advantages of both the methods and thus demonstrates robustness on geometric and image processing attacks [1][2][3][4][5][6][7][8]. Though the traditional watermarking methods provide good computing speed, they didn't automatically balance the invisibility and robustness because the said features will have conflict by nature with each other.…”

Section: Introductionmentioning

confidence: 99%

Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

Latha¹,

Reddy²,

Damodaram³

2019

IJITEE

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Cuckoo search algorithm is an efficiently designed algorithm for optimization based on the behavior of blood parasitism of Cuckoo species. The main advantages of Cuckoo Search algorithm are its simplicity, less computational time and efficiency. With said advantages, a novel method on video watermarking using Cuckoo search algorithm in DWT-SVD transform domain is proposed. SSIM, BER are used for fitness function in optimization function. The method proposed uses secret share method to achieve more security of watermark. The experimental results prove that the proposed video watermarking method provides good imperceptibility and more robust to attacks compared to few related methods

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Section: Introductionmentioning

confidence: 99%

Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

Latha¹,

Reddy²,

Damodaram³

2019

IJITEE

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“…Transform domain techniques provide greater levels of invisibility, as well as robustness against a variety of attacks in comparison with spatial domain techniques [36; 38]. Transform domain watermarking techniques have been developed using discrete wavelet transform (DWT) [11; 39], discrete Fourier transform (DFT) [5], discrete cosine transform (DCT) [23; 29] or matrix decompositions, including singular value decomposition (SVD) [16], QR decomposition [21], LU decomposition [15], Schur decomposition [32] and Hessenberg decomposition [37]. Several watermarking schemes which use more than one transform domain technique in order to improve the performance of the watermarking method have been proposed and the combination of these transformations may compensate for each other's drawbacks [30].…”

Section: Introductionmentioning

confidence: 99%

“…The host colour images and the watermark image measure the feasibility and robustness capabilities of the proposed colour image watermarking scheme, the peak signal-to-noise ratio (PSNR)[1] and the structural similarity index measure (SSIM) [7] are used to evaluate the invisibility of the reconstructed watermarked colour image. Meanwhile, normalised cross-correlation (NC)[21] is utilised to evaluate the similarity between the corresponding final watermark image and the original watermark image. The performance metrics are mathematically defined as follows.…”

mentioning

confidence: 99%

Colour Image Blind Watermarking Scheme Based on Fast Walsh Hadamard Transform and Hessenberg Decomposition

Abodena¹,

Agoyi²

2018

STUD INFORM CONTROL

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Colour image watermarking has become one of the most important algorithms for copyright protection. The following paper will present an innovative scheme for watermarking blind colour images using the discrete wavelet transform (DWT), fast Walsh Hadamard transform (FWHT) and the Hessenberg decomposition as its basis. First, two-level DWT followed by FWHT are used to decompose the host image's red channel. Next, the FWHT coefficients are split into 4 × 4 non-overlapping blocks. Then, each selected block is decomposed using Hessenberg decomposition, where the first row, first column element of the upper Hessenberg matrix H is quantified to embed the watermark information. Peak signalto-noise ratio, normalized cross-correlation and structural similarity index measure are used to evaluate the feasibility and the robustness. The experimental results have demonstrated that the proposed watermarking scheme is highly invisible with PSNR > 40 dB, for several watermarked colour images, with a capacity of 4096 bits and execution time of 0.7415s. The proposed watermarking scheme is also highly resistant to both common image processing and geometrical attacks such as filtering, JPEG2000, noise adding, cropping, scaling, blurring and sharpening, and others.

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“…The matrix decomposition can be used to extract the geometric features of an image, which is more robust against geometric attacks. Therefore, the image watermarking method based on combined DWT and matrix decomposition take the advantages of DWT and matrix decomposition and thus robust against both geometric attacks and image processing attacks [2,[15][16][17][18][19][20][21]. These traditional image watermarking methods have advantages in terms of high computing speed, but they cannot balance the invisibility and robustness automatically because invisibility and robustness are in conflict to each other.…”

Section: Introductionmentioning

confidence: 99%

Optimised blind image watermarking method based on firefly algorithm in DWT‐QR transform domain

Guo

Goel

2017

IET Image Processing

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Firefly algorithm (FA) is one of the newly developed nature inspired optimisation algorithm, inspired by the flashing behaviour of fireflies that a firefly tends to be attracted towards other fireflies with higher brightness. Thus FA has two advantages: local attractions and automatic regrouping. Based on these good properties, a novel image watermarking method based on FA in discrete wavelet transform (DWT)-QR transform domain is proposed in this study. Structural similarity index measure and bit error rate are used in the objective function to trade-off invisibility and robustness. The experiment results show that the proposed image watermarking method not only meet the need of invisibility, but also has better or comparable robustness as compared with some related methods.

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LWT- QR decomposition based robust and efficient image watermarking scheme using Lagrangian SVR

Cited by 40 publications

References 22 publications

Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

Robust Video Watermarking using Secret Sharing and Cuckoo Search Algorithm

Colour Image Blind Watermarking Scheme Based on Fast Walsh Hadamard Transform and Hessenberg Decomposition

Optimised blind image watermarking method based on firefly algorithm in DWT‐QR transform domain

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