Copyright protection of multiple CT images using Octonion Krawtchouk moments and grey Wolf optimizer

被引:8
|
作者
Yamni, Mohamed [1 ]
Daoui, Achraf [2 ]
Karmouni, Hicham [1 ]
Elmalih, Sarah [3 ]
Ben-fares, Anass [1 ]
Sayyouri, Mhamed [2 ]
Qjidaa, Hassan [1 ]
Maaroufi, Mustapha [3 ,4 ]
Alami, Badreeddine [3 ,4 ,5 ]
Jamil, Mohammed Ouazzani [6 ]
机构
[1] Sidi Mohamed Ben Abdellah Fez Univ, Fac Sci, Lab Elect Signals & Syst Informat, Fes, Morocco
[2] Sidi Mohamed Ben Abdellah Fez Univ, Natl Sch Appl Sci, Lab Engn Syst & Applicat, Fes, Morocco
[3] Sidi Mohamed Ben Abdellah Univ, Fac Med & Pharm, Clin Neurosci Lab, Fes, Morocco
[4] Univ Hosp Fez, Dept Radiol & Clin Imaging, Fes, Morocco
[5] Sidi Mohamed Ben Abdellah Univ, Fac Med & Pharm, Dept Biophys & Clin MRI Methods, BP 893,Km 2-200,Sidi Hrazem Rd, Fes 30000, Morocco
[6] FSI Private Univ Fez UPF, Fac Engn Sci, Syst & Sustainable Environm Lab SED, Fes, Morocco
关键词
D O I
10.1016/j.jfranklin.2023.03.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a novel Octonion Krawtchouk Moments (OKMs) transform to deal with a set of images in a compact manner, and based on this transform, a local zero-watermarking scheme is proposed to protect the copyright of CT medical images. The scheme first annotates regions of interest (ROIs) on seven medical images and then uses the OKMs of these ROIs to construct a single feature image called zero-watermark. This scheme adopts the gray Wolf Optimizer (GWO) algorithm to have a blind nature and to improve robustness against common image processing manipulations and attacks (zero -watermarking requirements). In addition, our scheme uses the trained U-net (R231) model to reduce the search space for the GWO algorithm and prevent this algorithm from getting stuck in a local optimal solution. The experimental results show that the proposed method is very robust against common image processing manupilations and attacks and has superiority compared with superb other zero-watermarking methods.(c) 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:4719 / 4752
页数:34
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