A DWT-SVD based adaptive color multi-watermarking scheme for copyright protection using AMEF and PSO-GWO. (15th April 2021)

• Record Type: Journal Article
• Authors: Shen, Yuxin; Tang, Chen; Xu, Min; Chen, Mingming; Lei, Zhenkun
• Is Part Of: Expert systems with applications. Volume 168(2021)
• Publication Date: 2021-04-15
• Subjects: Color multi-watermarking -- Adaptive multiple embedding factors (AMEF) -- Hybrid particle swarm optimization and grey wolf optimizer (PSO-GWO) algorithm -- Discrete wavelet transform (DWT) -- Singular value decomposition (SVD); Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.114414
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: We propose a novel algorithm to define the embedding regions and embedding strengths. Embedding strengths are optimized using a hybrid optimization algorithm. The cost function assures a pre-defined invisibility while maximizing robustness. The proposed scheme achieves all requirements and outperforms the existing methods. This scheme is applicable to the copyright protection for multi-watermarking. Abstract: Color multi-watermarking is a challenge in the field of copyright protection, and the key in the color multi-watermarking technology is how to determine the optimal embedding regions and embedding strengths to achieve the trade-off among multiple watermarks while maintaining great invisibility, sufficient robustness, and large capacity. In order to tackle these problems, an adaptive multiple embedding factors (AMEF) algorithm for calculating the optimal embedding regions and the optimal embedding strengths is proposed in this paper to embed multiple color watermarks simultaneously. In the presented AMEF algorithm, we propose that the optimal embedding regions are determined by the contrast function of different blocks. Then we determine the multiple embedding strengths to depend on the weighted ratio of the contrast values of blocks and the eigenvalues of different marks. Furthermore, in order to calculate the weight value in the AMEF algorithm, we define a single objective function and utilize a hybrid particle swarm optimization and grey wolf optimizer (PSO-GWO) algorithm to optimize the objective function. In this work, by the use of the discrete wavelet transform (DWT), singular value decomposition (SVD) and AMEF, four encrypted color watermarks are inserted into the selected regions of the color (normal or medical) host image, simultaneously. Then watermarked host image is tested under various attacks and compared to other recent existing schemes. The experimental results demonstrate that the proposed scheme can effectively achieve the trade-off among the invisibility, robustness and capacity, simultaneously. And from the comparison results, the proposed scheme possesses high security, large capacity, and strong robustness against various attacks while maintaining good invisibility.