Abstract
This study reviews the superiority and limitations of the Singular Value Decomposition (SVD)-based video watermarking scheme. First applies key frame selection to the video sequence to obtain an appropriate video frame for the purpose of watermark embedding in this paper. The Fibonacci-Lucas image transformation scrambles the grayscale watermark image before the embedding process. The former scheme satisfies the imperceptibility and robustness aspects. However, it can suffer from the False-Positive-Problem (FPP) in which a counterfeit watermark image can be easily reconstructed by a malicious attacker. This study presents a new technique for overcoming the FPP of the aforementioned scheme. The proposed method embeds the principal components of the watermark image rather than the Singular Value Matrix (SVM) into the host video. As results, the proposed methods yield promising results in terms of imperceptibility as well as robustness. At the same time, it solves the FPP. A theoretical analysis of embedded watermark information is also provided in this work. The theoretical analysis meets the experimental-based results in the SVD-based video watermarking scheme.
Highlights
The usage of multimedia data has grown enormously in recent years
The proposed method embeds the principal components of the watermark image rather than the Singular Value Matrix (SVM) into the media cover
The scaling factor plays an important role in the Singular Value Decomposition (SVD)-based image/video watermarking schemes
Summary
The usage of multimedia data has grown enormously in recent years. One example of multimedia usage is multimedia data communication via computer networks, the internet, cloud service, as well as the Internet-of-Things (IoT) devices. The proposed method overcomes the FPP in [13] by inserting the principal components of the watermark image into the host or cover media This works well and achieves impressive results for satisfying the imperceptibility and robustness aspects that can be directly applied for securing the multimedia data communication via the IoT environment. Even though the quality of reconstructed image Ais less than the original image, we can still recognize Aas Lena image This is the main reason most typical SVD-based image watermarking schemes embed the SVM into the host image. These figures show the reconstructed images are visually identical to that of the original Lena image This usability motivates the proposed method to deliver secure SVD-based image watermarking. The proposed method renders the watermark information into the largest singular value of each host image block
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