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Article type: Research Article
Authors: Rahman, Atta; *
Affiliations: Department of Computer Science, College of Computer Science and Information Technology (CCSIT), Imam Abdulrahman Bin Faisal University (IAU), Dammam, Saudi Arabia
Correspondence: [*] Corresponding author. Atta Rahman, Department of Computer Science, College of Computer Science and Information Technology (CCSIT), Imam Abdulrahman Bin Faisal University (IAU), P.O. Box 1982, Dammam, Saudi Arabia. E-mail: aaurrahman@iau.edu.sa.
Abstract: In this research, a novel block-based, integer wavelet transform (IWT) domain digital image watermarking scheme for optimum information embedding using a Fuzzy Rule Based System (FRBS) is proposed. There are three famous conflicting parameters in digital image watermarking, namely, robustness, imperceptibility and payload are linked with each other and a change in one parameter affects others and vice versa. That’s why it is hard to optimize them, jointly because of the inherent non-linearity and in the literature, any pair of parameters is optimized while third is assumed as fixed. In this proposal, this non-linear problem is solved using FRBS by using the logical relationship among three parameters and it consequently suggests the image from the image-bank that may convey the desired payload (capacity) with maximum imperceptibility and robustness. The proposed FRBS is two-fold. Firstly, selection of candidate image blocks from the given image and secondly selection of the candidate coefficients from the already chosen blocks for embedding the desired payload. Images having coefficients greater than a certain threshold are chosen and the payload is embedded. Consequently, the watermarked images are passed through various attacks and the image with maximum robustness is selected. The effectiveness of the proposed scheme is demonstrated through MATLAB simulations and comparison with state-of-the-art techniques.
Keywords: Digital image watermarking, IWT, optimum embedding, PSNR, block-based
DOI: 10.3233/JIFS-162405
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 553-564, 2019
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