A Robust Image Hashing Algorithm Resistant Against Geometrical Attacks

This paper proposes a robust image hashing method which is robust against common image processing attacks and geometric distortion attacks. In order to resist against geometric attacks, the log-polar mapping (LPM) and contourlet transform are employed to obtain the low frequency sub-band image. Then the sub-band image is divided into some non-overlapping blocks, and low and middle frequency coefficients are selected from each block after discrete cosine transform. The singular value decomposition (SVD) is applied in each block to obtain the first digit of the maximum singular value. Finally, the features are scrambled and quantized as the safe hash bits. Experimental results show that the algorithm is not only resistant against common image processing attacks and geometric distortion attacks, but also discriminative to content changes

A New Digital Watermarking Algorithm Using Combination of Least Significant Bit (LSB) and Inverse Bit

In this paper, we introduce a new digital watermarking algorithm using least significant bit (LSB). LSB is used because of its little effect on the image. This new algorithm is using LSB by inversing the binary values of the watermark text and shifting the watermark according to the odd or even number of pixel coordinates of image before embedding the watermark. The proposed algorithm is flexible depending on the length of the watermark text. If the length of the watermark text is more than ((MxN)/8)-2 the proposed algorithm will also embed the extra of the watermark text in the second LSB. We compare our proposed algorithm with the 1-LSB algorithm and Lee's algorithm using Peak signal-to-noise ratio (PSNR). This new algorithm improved its quality of the watermarked image. We also attack the watermarked image by using cropping and adding noise and we got good results as well.Comment: 8 pages, 6 figures and 4 tables; Journal of Computing, Volume 3, Issue 4, April 2011, ISSN 2151-961

A blind robust watermarking scheme based on svd and circulant matrices

Multimedia security has been the aim point of considerable research activity because of its wide application area. The major technology to achieve copyright protection, content authentication, access control and multimedia security is watermarking which is the process of embedding data into a multimedia element such as image or audio, this embedded data can later be extracted from, or detected in the embedded element for different purposes. In this work, a blind watermarking algorithm based on SVD and circulant matrices has been presented. Every circulant matrix is associated with a matrix for which the SVD decomposition coincides with the spectral decomposition. This leads to improve the Chandra algorithm [1], our presentation will include a discussion on the data hiding capacity, watermark transparency and robustness against a wide range of common image processing attacks.Comment: 12 pages, 6 figures, 5 tables, Second International Conference on Computational Science & Engineering (CSE - 2014

A Blind Multiple Watermarks based on Human Visual Characteristics

Digital watermarking is an alternative solution to prevent unauthorized duplication, distribution and breach of ownership right. This paper proposes a watermarking scheme for multiple watermarks embedding. The embedding of multiple watermarks use a block-based scheme based on human visual characteristics. A threshold is used to determine the watermark values by modifying first column of the orthogonal U matrix obtained from Singular Value Decomposition (SVD). The tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value. The results show that our proposed multiple watermarks scheme exhibit robustness against signal processing attacks. The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks

Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8�8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack. Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved

Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection