Robustness Improvement Against a Non-Geometrical Attacks of Lifting SchemeBased Image Watermarking through Singular Value and Schur Decompositions

Marjuni, Aris; Nurhayati, Oky Dwi

doi:10.22266/ijies2021.0831.20

Cited by 3 publications

(4 citation statements)

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“…To determine the watermarked model imperceptibility, Mean Square Error (MSE) metrics are shown in Eq. ( 4) [24][25][26].…”

Section: Extraction Algorithmmentioning

confidence: 99%

Data Hiding in 3D Model Based on Surface Properties

Ali

2023

Iraqi Journal of Science

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Data hiding strategies have recently gained popularity in different fields; Digital watermark technology was developed for hiding copyright information in the image visually or invisibly. Today, 3D model technology has the potential to alter the field because it allows for the production of sophisticated structures and forms that were previously impossible to achieve. In this paper, a new watermarking method for the 3D model is presented. The proposed method is based on the geometrical and topology properties of the 3D model surface to increase the security. The geometrical properties are based on computing the mean curvature for a surface and topology based on the number of edges around each vertex, the vertices that have negative mean curvature and an odd number of edges around the vertex are selected for embedding. Selecting the vertex with negative mean curvature value means the vertex located in the deep region of the surface, so it not noticeable change to human eyes. To evaluate the performance of the proposed algorithm, the PSNR, and CF are used as a measurement to evaluate the visibility and robustness of the 3D watermarked model. The experimental results have shown the proposed algorithm has good imperceptibility where the PSNR reach up to 44.41 and robustness against attack where the CF is one in many cases.

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“…To determine the watermarked model imperceptibility, Mean Square Error (MSE) metrics are shown in Eq. ( 4) [24][25][26].…”

Section: Extraction Algorithmmentioning

confidence: 99%

Data Hiding in 3D Model Based on Surface Properties

Ali

2023

Iraqi Journal of Science

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“…SVD provides an easy way to divide a matrix, which might consist of some data in simpler matrices. Let I be the NN of real matrix R with rank r, where r  N. The SVD of the matrix I is formulated in the next equation as a factorization of eigendecomposition matrices U, S, and V [15] as follows:…”

Section: Theoretical Review 21 Singular Value Decomposition (Svd)mentioning

confidence: 99%

“…The Normalized Cross-Correlation (NCC) in the next equation is used to evaluate the recovered watermark image robustness [15]. This metric measures the similarity between the recovered watermark and the original watermark images.…”

Section: mentioning

confidence: 99%

“…Some hybrid methods based on SVD image watermarking have also been proposed in other domains. The SVD hybrids with lifting wavelet transform have been proposed in [13], SVD hybrids with Discrete Wave Transformation (DWT) and Hessenberg decomposition have been proposed in [14], and also SVD hybrids with lifting scheme on SVD and Schur Decomposition are proposed in [15]. The other existing hybrid schemes on SVD have been also observed in [16] through their survey, where the SVD algorithm has been widely combined with some methods such as invariant wavelet, particle swarm optimization, human visual system, genetic algorithm, evolutionary algorithm, firefly algorithm, artificial bee colony, and k-Means Algorithm to achieve better performance.…”

Section: Introductionmentioning

confidence: 99%

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Visual Quality Improvement of Watermarked Image Based on Singular Value Decomposition Using Walsh Hadamard Transform

Marjuni

Fanani

Nurhayati

2023

Cybernetics and Information Technologies

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Embedding the watermark is still a challenge in image watermarking. The watermark should not reduce the visual quality of the image being watermarked and hard to distinguish from its original. Embedding a watermark of a small size might be a good solution. However, the watermark might be easy to lose if there is any tampering with the watermarked image. This research proposes to increase the visual quality of the watermarked image using the Walsh Hadamard transform, which is applied to the singular value decomposition-based image watermarking. Technically, the watermark image is converted into a low bit-rate signal before being embedded in the host image. Using various watermark sizes, experimental results show that the proposed method could produce a good imperceptibility with 47.10 dB on average and also gives robustness close to the original watermark with a normalized correlation close to 1 on average. The proposed method can also recognize the original watermark from the tampered watermarked image at different levels of robustness.

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