Dual secure robust watermarking scheme based on hybrid optimization algorithm for image security

被引：2

作者：

Alam S. ^{[1
]}

Ahmad T. ^{[1
]}

Doja M.N. ^{[1
]}

Pal O. ^{[1
,2
]}

机构：

[1] Department of Computer Engineering, Faculty of Engineering and Technology, Jamia Millia Islamia, -110025, New Delhi

[2] Ministry of Electronics and Information Technology, Government of India, New Delhi

来源：

Personal and Ubiquitous Computing | 2024年 / 28卷 / 01期

关键词：

Hybrid optimization algorithm; Image authentication; Image security; Subbands; Watermarking;

D O I：

10.1007/s00779-021-01597-2

中图分类号：

学科分类号：

摘要：

Digital watermarking is a technology that allows users to add copyright notifications or other confirmation messages to digital media. Image recognition is one of the applications of digital watermarking, which is used to identify digital images. The goal is not to prevent theft or theft of content but to provide a means of identifying the images and ensuring the integrity of the image. This paper proposes a dual security robust watermarking (DSRW) method based on a hybrid optimization algorithm for image protection in the DWT domain used in the IoT perceptive layer. First, we introduce the redistributed differential wavelet transform (RI-DWT) to induce the LH and HL subbands. Second, we proposed the advanced cat swarm optimization (ICSO) algorithm to find the best module for watermark inclusion. After the best batch selection, the inclusion procedure adds the binary score to the selected first-level approximate subband of the RI-DWT for each selected module. Optimal QR decomposition is used to estimate a single value in the image matrix. The main objective of the proposed watermarking plan is to ensure high robustness and security. The simulation results examine the significance of the proposed scheme and the validity of the proposed methods. The experiments are conducted to check various common image processing attacks, and the watermark extraction process generates high-quality image after different attacks. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021.

引用

页码：193 / 205

页数：12

共 30 条

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