SVD and Neural Network Based Watermarking Scheme

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2014

The validation of images taken by digital cameras has become a great concern as the digital photography is gaining rapid popularity. So, due to lack of protection of digital content as they can be easily duplicated and disseminated without the owner's consent , publishers, artists, and photographers, however, are unwilling to distribute images or other data over the Internet. Therefore, to protect confidential images we propose an efficient digital watermarking technique to deal with this difficult issue. In the proposed technique, the image is first converted into YCbCr from RGB domain then watermark is embedded in Y component of YCbCr using Discrete Wavelet Transform and Singular ValueDecomposition (SVD). The results show that our algorithm is resistant toward various attacks.

IEEE Access, 2021

Watermarking is an important technique for protecting sensitive e-multimedia data and intellectual property. Watermarking techniques are used for many applications such as ownership protection, which is a popular area of research as compared to others such as authentication and local temper localization. There are many image watermarking schemes that have been recently published based on the frequency domain as it can fulfill watermarking requirements such as high robustness and imperceptibility. Singular-value decomposition (SVD) is one of them and is used in many frequency transform-based image watermarking schemes due to its stability and mathematical simplicity. However, there are many schemes that lack robustness against malicious cyberattacks, whereby the watermarks are easy to detect and destroy. Consequently, the proposed watermarking schemes became more complicated and cannot resist various geometric and non-geometric attacks. Thus, there are many existing hybrid SVD-based image watermarking schemes found be insecure. As there is also a lack of in-depth reviews in this domain, the focus of this paper is the analysis of the state-of-the-art in hybrid SVD-based image watermarking. We perform efficiency comparisons to highlight various security problems, open issues, and research gaps. Based on our findings, we additionally provide some recommendations for the development of more robust schemes in the future. This paper provides essential information for researchers and practitioners alike to advance the field of image watermarking. INDEX TERMS Embedding, extraction, frequency domain, image watermarking, singular-value decomposition (SVD).

This paper, aims at embedding an invisible watermark into a digital image using the Singular Value Decomposition (SVD). The technique uses the U matrix of the SVD and modifies two of its value according to the watermark bit. The proposed technique is a modification of a recent scheme[1] proposed by B. Chandra Mohan and S. Srinivas Kumar in terms of Bit Correct Rate and robustness. Superior results are obtained when the watermarked image is attacked by histogram equalization, cropping, setting and resetting LSB plane, linear and non-linear filtering, noise and compression.

As the popularity of digital media is growing, and world is becoming smaller, all due to the internet connectivity and WWW phenomena, the copyright protection of intellectual properties have become a necessity for prevention of illegal copying and content integrity verification. Thus newer data hiding techniques that satisfy the requirements of imperceptibility, robustness, capacity, or data hiding rate and security of the hidden data etc. are being developed. So we go for digital image watermarking which is a method of authentication data (which is the presence of logo here) embedding in image characteristics with expectation to show resiliency against different type of unintentional or deliberate attacks. Here wavelet transform plays the role of an efficient tool due to its multi-resolution capability. Along with this wavelet transform we mix up another very strong mathematical tool called the singular value decomposition (SVD). Though till date both of them have individually been used as a tool for watermarking of digital media, very few works have utilized their skills in tandem, especially in this area. Our work here by focuses on using both of them together to provide a hybrid technique developed for protection of the intellectual property with better robustness against the popular malicious attacks. This we have seen practically by attacking the watermarked image against simulated attacks and recovering the logo from it.

Computing Research Repository, 2008

We propose a novel scheme for watermarking of digital images based on singular value decomposition (SVD), which makes use of the fact that the SVD subspace preserves significant amount of information of an image, as compared to its singular value matrix, Zhang and Li (2005). The principal components of the watermark are embedded in the original image, leaving the detector with a complimentary set of singular vectors for watermark extraction. The above step invariably ensures that watermark extraction from the embedded watermark image, using a modified matrix, is not possible, thereby removing a major drawback of an earlier proposed algorithm by Liu and Tan (2002).

Asian Journal of Computer Science and Technology, 2019

An enormous growth of multimedia information in the internet has given rise to varied unauthorized use and modification. This authenticity issue is equally a limitation both in the defense data transmission and secured transmission. Digital watermarking is one of the legitimate solutions to the above problem since it makes possible validation and secure transmission of secret data. This paper presents a robust and secure digital image watermarking scheme that can be used for copyright protection. The scheme involves Lifting Wavelet Transform (LWT) and Singular Value Decomposition (SVD). The latest approach to wavelet transform is the Lifting Wavelet Transform and the significant transform technique for robust digital image watermarking is Singular Value Decomposition. The results are cross-validated by using inverse LWT and SVD. The digital signature mechanism is used to generate and embed a digital signature after the watermark is embedded, then the ownership is authenticated befor...

2008

As the popularity of digital media is growing, and world is becoming smaller, all due to the internet connectivity and WWW phenomena, the copyright protection of intellectual properties have become a necessity for prevention of illegal copying and content integrity verification. Thus newer data hiding techniques that satisfy the requirements of imperceptibility, robustness, capacity, or data hiding rate and security of the hidden data etc. are being developed. So we go for digital image watermarking which is a method of authentication data (which is the presence of logo here) embedding in image characteristics with expectation to show resiliency against different type of unintentional or deliberate attacks. Here wavelet transform plays the role of an efficient tool due to its multi-resolution capability. Along with this wavelet transform we mix up another very strong mathematical tool called the singular value decomposition (SVD). Though till date both of them have individually been used as a tool for watermarking of digital media, very few works have utilized their skills in tandem, especially in this area. Our work here by focuses on using both of them together to provide a hybrid technique developed for protection of the intellectual property with better robustness against the popular malicious attacks. This we have seen practically by attacking the watermarked image against simulated attacks and recovering the logo from it.

Journal of Electronic Imaging, 2010

Watermarking algorithms of digital images based on singular value decomposition (SVD) have been proposed recently. Most SVD-based watermarking techniques use singular values as the embedding watermark information. These SVD-based techniques are advantageous for watermarking images since slight changes in the singular values do not affect significantly 1 the image quality. However it has been reported that these SVD-based watermarking algorithms as implemented suffer from a very high probability of false positive detections of watermarks. In this paper, the false positive detection vulnerability of two recent SVD-based watermarking schemes is exposed. Two solutions are proposed to mitigate this vulnerability without changing the design principle of these watermarking algorithms.

We propose a novel scheme for watermarking of digital images based on singular value decomposition (SVD), which makes use of the fact that the SVD subspace preserves significant amount of information of an image, as compared to its singular value matrix, . The principal components of the watermark are embedded in the original image, leaving the detector with a complimentary set of singular vectors for watermark extraction. The above step invariably ensures that watermark extraction from the embedded watermark image, using a modified matrix, is not possible, thereby removing a major drawback of an earlier proposed algorithm by .

A b s t r a c t This paper proposes a new method for digital watermarking using secret key and singular vector decomposition (SVD). Instead of embedding information in row one, column one of all feature matrices, we embed information only into blocks which have high contrast in order to improve the quality of the embedded image. Moreover, we use a secret key in embedded watermarking process to increase the security of the method, in which one can only extract information when possessing the secret key. The results show that our method outperforms the pure SVD-based method in the quality of images and is more robust against security attacks.