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Enhanced Invisibility and Robustness of Digital Image Watermarking Based on DWT-SVD
Author(s) -
Ali Alzahrani
Publication year - 2022
Publication title -
applied bionics and biomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.397
H-Index - 23
eISSN - 1754-2103
pISSN - 1176-2322
DOI - 10.1155/2022/5271600
Subject(s) - digital watermarking , robustness (evolution) , singular value decomposition , invisibility , computer science , artificial intelligence , discrete wavelet transform , watermark , computer vision , normalization (sociology) , pixel , pattern recognition (psychology) , wavelet , image (mathematics) , wavelet transform , gene , anthropology , chemistry , biochemistry , sociology
The propagation of digital media over the Internet has helped improve digitization, which has given an excessive lead to copyright issues. Digital watermarking techniques have been applied to address copyright issues. In research, a system is being developed to handle veracious types of watermarked attacks, for obtaining extreme security and an adequate level of visibility and robustness. The discrete wave transform (DWT) and singular value decomposition (SVD) approaches were applied to analyze veracious types of attacks. The DWT method was used to embed the host image in four levels; this level was processed using the SVD method. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were applied to measure the invisibility, and the normalization correlation (NC) was used to examine the robustness of watermarked images. The empirical results showed that the proposed DWT-SVD achieved superior accuracy in identifying the various attacks. The proposed DWT-SVD performance was confirmed during the training process, and the proposed system was shown to have high invisibility and robustness against various types of attacks on watermarked images. Finally, the results of the proposed system were compared to existing systems, and it was shown that DWT-SVD achieved better performance in terms of pixel-value modification attacks.

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