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An optimized color image watermarking algorithm with stationary wavelet transform and singular value decomposition has been proposed in this work. The algorithm uses two watermarks to address the issues of copyright protection and tamper localization. A gray-scale image watermark is embedded in the transform domain of the green plane of the cover image to address the issue of copyright protection. A binary logo watermark is inserted in the spatial domain of the blue plane of the cover image by the least significant bit approach. It helps to locate the visible and invisible tampers in the cover image. This work is optimized through the genetic algorithm (GA) to achieve better perceptual quality and robustness. A novel fitness function has been proposed to use with the GA to figure out an optimal scaling factor for the embedding process. The strength of the algorithm has been examined by enforcing several attacks on the watermarked image. The embedding capacity of the algorithm and the time complexity of the proposed fitness function are compared with other existing works. [ABSTRACT FROM AUTHOR]

Watermarking is a technique which offers more robustness and good imperceptibility. Even if the algorithmic principle is public or the existence of hidden information is known, it is difficult to attacker to destroy the embedded watermark without degrading the watermarked media severely. In existence, non-blind watermarking (NBW) schemes and different combinations of techniques are proposed for watermarking procedure. But these methods failed to provide the good imperceptibility, lack of robustness and embedding capacity standards, respectively. Thus, to overcome this problem, a hybrid algorithm for blind watermarking (BW) is proposed, which utilizes redundant discrete wavelet transform (RDWT), discrete cosine transform (DCT) and singular value decomposition (SVD) together to have the advantages of all three. In addition, optimization of proposed RDWT-DCT-SVD is obtained using a new bio-inspired algorithm called Porcellio Scaber algorithm (PSA). Thus, the visual perception of extracted watermark image also good enough by maintaining the robustness against various image attacks. Experiments are carried out to test the proposed BW algorithm and it is successful under various geometrical and non-geometrical attacks. Finally, the performances of proposed BW using RDWT-DCT-SVD with PSA optimization is compared with various existing BW approaches in terms of various quality metrics like peak signal to noise ratio (PSNR), structural similarity (SSIM) index, root mean square error (RMSE) and normalized correlation coefficient (NCC). [ABSTRACT FROM AUTHOR]

This article introduces the hybrid encryption (HE)-based CIW using combined integer wavelet transform (IWT) with discrete cosine transform (DCT), where the HE performs on watermark image to encrypt the data securely before embedding it into cover image while both IWT, and DCT are used to extract the features from cover RGB image. In addition, the grey-wolf optimization (GWO) is employed for extracting the enhanced features obtained from IWTDCT. Then, LSB approach is employed for embedding the encrypted watermark image into the cover image, here after the proposed method is denoted as OHE-based IWT-DCT with LSB. Finally, the watermarked image is obtained using inverse transforms of IWT, and DCT with postprocessing operations. The simulations carried out on standard test images discloses the superiority of proposed OHE-based IWT-DCT with LSB approach as compared to stateof-art CIW approaches in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, mean square error (MSE), normalized cross correlation (NCC) and unified averaged changed intensity (UACI) values. [ABSTRACT FROM AUTHOR]

Digital Watermarking has evolved as one of the latest technologies for digital media copyright protection. Watermarking of images can be done in many ways and one of the proposed algorithms for image watermarking is by utilizing Fuzzy Logic. It is similar to the concept of a Fuzzy set, each element can be defined by an ordered pair, in which one is the value and other is the membership function value. Fuzzy logic systems can explain inaccurate information and explain their decisions. Fuzzy inference system is the simplest way of performing Fuzzy Logic. In the proposed method, three Fuzzy inference models are used to generate the weighing factor for embedding the watermark and input to the Fuzzy Inference System is taken from the Human Visual System model. The Performance measures used in the Process are Peak Signal to Noise Ratio, Normalized Cross Correlation. The Proposed algorithm is immune to various Image Processing attacks. [ABSTRACT FROM AUTHOR]

• Utilization of PCA in R-DW domain with IGWO algorithm for the applications of blind image watermarking. As per our best knowledge, this combining methodology has not been applied for watermarking applications before. • An improved methodology of BW to the existing R-DW based approaches [4–7] presented in the literature. • A new framework on BW using proposed PCA-R-DW with novel embedding and extraction process is proposed. Further, for the first time IGWO algorithm is utilized as an optimization for the applications of BW. • A comparative analysis is provided to show the robustness of proposed BW algorithm with R-DW [7] , Takore et al. [8] , wavelet with PSO [9] , integer wavelet transform (IWT) with PSO [10] and PCA_R-DW without IGWO algorithm. The frequency of digital data transmission or sharing online has heavily increased due to the number of people regularly accessing the internet. This guide explores how easily copyright can be breached on a large scale. Digital multimedia in the form of images, text, audio and video can easily be forged, faked and then shared for profit. To address this issue, digital watermarking has been introduced as a possible solution. In this guide, an optimized blind image watermarking approach based on principal component analysis (PCA) in redundant discrete wavelet (R-DW) domain is proposed. In addition, several attacks are applied to a watermarked image by extracting the message from the attacked image to show the robustness of the proposed PCA-R-DW scheme. Furthermore, an improved grey-wolf optimizer (IGWO) algorithm which has emerged as an efficient meta-heuristic optimization technique is utilized to optimize the performance of the proposed PCA-R-DW blind watermarking (BW) approach. Extensive comparison of test results with conventional BW approaches show the robustness of the proposed framework in terms of quality metrics such as normalized correlation coefficient (NCC), peak signal-to-noise ratio (PSNR), mean square error (MSE) and structural similarity (SSIM) index. [ABSTRACT FROM AUTHOR]