Performance Evaluation of Robust Watermarking Using DWT-SVD and RDWT-SVD

Kadian, Poonam; Arora, Nidhi; Arora, Shaifali Madan

doi:10.1109/spin.2019.8711681

Cited by 20 publications

(14 citation statements)

References 10 publications

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“…For further decomposition, any of the sub-bands are selected and hence divide into four levels. The decomposition method is replicated until the required levels of decomposition are reached [32]. The maximum degree of decomposition seems to be the intensity of the watermarked image [33].…”

Section: Dwtmentioning

confidence: 99%

An Efficient Watermarking Approach Based on LL and HH Edges of DWT–SVD

Yasmeen

Uddin

2021

SN COMPUT. SCI.

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Digital watermarking is playing a vital role in the improvement of authentication, security, and copyright protection in today’s digital transformation. The performance of this technique is shown to be impressive around the globe. Text, audio, video, and image data are acted as watermarks in the digital platform. In this article, a hybrid watermarking scheme is proposed to furnish the robustness and protection of digital data. This hybrid scheme is a form of discrete wavelet transform (DWT) and singular value decomposition (SVD). The embedding and extracting features are carried out through multi-level operations of DWT and SVD. Various attacks are added to the proposed method to justify the robustness of the watermark. In the end, the suggested approach is contrasted with existing methods to confirm the supremacy.

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Section: Dwtmentioning

confidence: 99%

An Efficient Watermarking Approach Based on LL and HH Edges of DWT–SVD

Yasmeen

Uddin

2021

SN COMPUT. SCI.

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“…The other method that can be used in place of SVD is Eigen Decomposition, but since every rectangular matrix has an SVD, it makes SVD decomposition method a more stable method than other methods. In the process of SVD an MxN sized image gets decomposed as a 2-D MxN matrix and then SVD is applied over this MxN matrix to obtain three matrices namely U, S and V. The diagonal values of S matrix are known as singular values of matrix A, whereas the columns of U and V matrices are termed as left and right singular values of A respectively [13,14]. Figure 3 illustrates decomposing of matrix A (MxN) resulting three SVD matrices as: A= USV T (1) Where U and V are square matrices and S is a rectangular matrix with the same dimensions as of matrix A.…”

Section: A Dwt (Discrete Wavelet Transform)mentioning

confidence: 99%

Role of Scaling Factor in Robust Digital Watermarking

Kadian¹,

Arora²,

Arora³

2019

IJITEE

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Digital watermarking has been identified as an efficient tool to provide copyright authentication and protection of digital data. Robustness and Imperceptibility are the two key parameters in designing of watermarking system. It is always desired to design a watermarking system that provides excellent robustness to malicious attacks and the watermark is invisible to human eyes. The robustness and imperceptibility can be controlled by choosing an effective scaling factor. Scaling factor decides on the amount of insertion of watermark in the host image. Higher the value of scaling factor more visible the watermark will be in watermarked image, this leads to poor imperceptibility. However the increase in scaling factor leads to a more robust watermarking system. Finding a trade-off among both is the key issue of research in this area. This paper aims at describing the effect of selection of scaling factor on robustness and imperceptibility by taking different values of scaling factor during each watermarking process. The empirical analysis done in this work shows robustness can be improved at the cost of imperceptibility and vice-versa.

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“…The validity and authenticity could become more vital if singular value decomposition (SVD) incorporate with DWT. Because of intrinsic algebraic properties and reduction of complexities, 7 the SVD shows trustworthiness in digital watermarking applications 8 . Upon considering the situation, this paper presents a robust hybrid watermarking approach through the fusion of DWT with SVD that yields the validity and imperceptibility of the watermarked image and gives robustness beyond numerous types of attacks.…”

Section: Introductionmentioning

confidence: 99%

A novel watermarking scheme based on discrete wavelet transform‐singular value decomposition

Yasmeen

Uddin

2022

Security and Privacy

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Due to the rapid advancement in information technology, individuals as well as organizations frequently transfer or share their digital content via cyberspace. The security and integrity of this digital content become a big concern, as any middleman can misuse or temper this content. Digital watermarking is a blessing to protect it from any unwanted tampering. Even though many researchers have implemented various watermarking approaches, but still ownership protection and reliability concerns are not fully mitigated. This paper proposes an improved novel hybrid watermarking scheme by combining discrete wavelet transform (DWT) with singular value decomposition (SVD) to minimize these concerns. At first, the host image is decomposed by multi‐level DWT and a two‐level SVD is applied to the fourth lower‐level coefficient (LL5) of the host image. Then the watermark is inserted into the specified sub‐band of the host image. The watermark is extracted in a reverse manner. The hybridization of DWT and SVD ensures that the watermarking technique performs better in terms of visual distortion and robustness. The outcomes of the experiment show that our proposed method is more robust, imperceptible, and secure than the existing DWT‐SVD based methods, even with a broad watermark scale.

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Performance Evaluation of Robust Watermarking Using DWT-SVD and RDWT-SVD

Cited by 20 publications

References 10 publications

An Efficient Watermarking Approach Based on LL and HH Edges of DWT–SVD

An Efficient Watermarking Approach Based on LL and HH Edges of DWT–SVD

Role of Scaling Factor in Robust Digital Watermarking

A novel watermarking scheme based on discrete wavelet transform‐singular value decomposition

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