A framework of hybrid metaheuristic H-Grey optimization for embedding factor decision-making in digital image watermarking on social media

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A framework of hybrid metaheuristic H-Grey optimization for embedding factor decision-making in digital image watermarking on social media

A framework of hybrid metaheuristic H-Grey optimization for embedding factor decision-making in digital image watermarking on social media

Author : Dr Priyanka

Year : 2024

Publisher : CRC Press

Source Title : Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making: Optimization Applications

Document Type :

Abstract

Nowadays, social media platforms are a great way to connect and communicate with people all around the world. Digital images are the primary media of communication. Transmission of digital images over social media applications comes across various security issues like unauthorized accessing, owner identity theft, tarnishing metadata, and so on. To address all these stated issues, in this chapter, a secured digital image watermarking scheme is proposed in the hybrid redundant discrete wavelet transform (RDWT) – singular value decomposition (SVD) domain to provide high visual quality and robustness of the images. Also, embedding strength parameter selection decision is made using a hybrid metaheuristic Harmony-Greywolf (H-Grey) optimization approach to balance trade-off watermarking characteristics. To ensure higher security, embedding positions can be selected using a cross-layer approach in RDWT-SVD domain, and before embedding, watermark is encrypted using a Latin square sequence. Experiments are conducted on the proposed scheme in terms of watermarking characteristics like imperceptibility, robustness, and security. The outcomes of the experimental results show higher performance.