Cited By
View all- Aldakheel EKhafaga DZaki MLashin NHamza HHosny K(2024)Fast encryption of color medical videos for Internet of Medical ThingsJournal of Real-Time Image Processing10.1007/s11554-024-01547-021:5Online publication date: 20-Sep-2024
Robust color image watermarking using multi-core Raspberry pi cluster
Authors: 
Khalid M. Hosny, Amal Magdi, Nabil A. Lashin, Osama El-Komy, 
Ahmad SalahAuthors Info & Claims
Pages 17185 - 17204
Abstract
Image authentication approaches have gotten a lot of interest recently as a way to safeguard transmitted images. Watermarking is one of the many ways used to protect transmitted images. Watermarking systems are pc-based that have limited portability that is difficult to use in harsh environments as military use. We employ embedded devices like Raspberry Pi to get around the PC’s mobility limitations. Digital image watermarking technology is used to secure and ensure digital images’ copyright by embedding hidden information that proves its copyright. In this article, the color images Parallel Robust watermarking algorithm using Quaternion Legendre-Fourier Moment (QLFM) in polar coordinates is implemented on Raspberry Pi (RPi) platform with parallel computing and C++ programming language. In the host image, a binary Arnold scrambled image is embedded. Watermarking algorithm is implemented and tested on Raspberry Pi model 4B. We can combine many Raspberry Pi’s into a ‘cluster’ (many computers working together as one) for high-performance computation. Message Passing Interface (MPI) and OpenMP for parallel programming to accelerate the execution time for the color image watermarking algorithm implemented on the Raspberry Pi cluster.
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© The Author(s) 2022.
Publisher
Kluwer Academic Publishers
United States
Publication History
Published: 01 May 2022
Accepted: 03 January 2022
Revision received: 25 August 2021
Received: 22 December 2020
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- Zagazig University
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Cited By
View all- Aldakheel EKhafaga DZaki MLashin NHamza HHosny K(2024)Fast encryption of color medical videos for Internet of Medical ThingsJournal of Real-Time Image Processing10.1007/s11554-024-01547-021:5Online publication date: 20-Sep-2024
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