Multiple Zero-Watermarking of Medical Images for Internet of Medical Things-Reference-Cited by-同舟云学术

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Multiple Zero-Watermarking of Medical Images for Internet of Medical Things

Published:2022 Issue: Volume:10 Page:38821-38831
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Magdy Mahmoud¹^ORCID,Ghali Neveen I.¹,Ghoniemy Said²,Hosny Khalid M.³^ORCID

Affiliation:

1. Department of Digital Media Technology, Future University in Egypt (FUE), New Cairo, Egypt

2. Department of Computer Systems, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

3. Department of Information Technology, Zagazig University, Zagazig, Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09751699.pdf?arnumber=9751699

Reference41 articles.

1. NPCR and UACI randomness tests for image encryption;wu;J Sel Areas Telecommun,2011

2. Fractional-order orthogonal Chebyshev Moments and Moment Invariants for image representation and pattern recognition

3. A two-dimensional mapping with a strange attractor

4. Fast computation of orthogonal Fourier–Mellin moments in polar coordinates

5. A kernel-based method for fast and accurate computation of PHT in polar coordinates

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1. A robust medical image zero-watermarking algorithm using Collatz and Fresnelet Transforms;Journal of Information Security and Applications;2024-09

2. Resnet50 and logistic Gaussian map-based zero-watermarking algorithm for medical color images;Neural Computing and Applications;2024-08-08

3. Integrating Fresnelet Transform and Spiking Cortical Model for robust medical image cryptosystem in zero-watermarking;Computers and Electrical Engineering;2024-08

4. New method of colour image encryption using triple chaotic maps;IET Image Processing;2024-06-26

5. Authenticating and securing healthcare records: A deep learning-based zero watermarking approach;Image and Vision Computing;2024-05

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