A reversible and imperceptible watermarking scheme for MR images authentication

Conference paper

Qasim, A, Meziane, F. and Aspin, R 2018. A reversible and imperceptible watermarking scheme for MR images authentication. 24th International Conference on Automation and Computing (ICAC). Newcastle Upon Tyne, UK 06 - 07 Sep 2018 IEEE Xplore. https://doi.org/10.23919/iconac.2018.8749000
AuthorsQasim, A, Meziane, F. and Aspin, R
TypeConference paper
Abstract

This paper presents a novel reversible and imperceptible watermarking technique to detect intentional and accidental alterations within brain Magnetic Resonance
(MR) images. Authentication data is embedded into the
informative part of the medical image using reversible
watermarking based on the Difference Expansion (DE)
method. Experimental results demonstrate that the proposed scheme, whilst completely reversible, can also achieve a watermarked image with low distortion. This is realized by encoding the watermark into ‘smooth’ regions inside the Region of Interest (ROI) of the image and through eliminating the need for location map required for extracting the concealed data and reconstructing the original unmodified image. Our proposed scheme delivers highly imperceptible watermarked images, at 92.9 - 97.98 dB Peak Signal to Noise Ratio (PSNR), and exceeds the others approaches presented in previous studies. Authenticity and integrity of medical images are also guaranteed through detecting subsequent modifications applied to the watermarked images. This enhanced security measure, therefore, enables the detection of image alterations, by a reversible and imperceptible approach, that may offer increased confidence in the digital medical practices.

KeywordsAuthentication; ; Integrity; ; Medical imaging; ; MRI; ; Reversible watermarking
Year2018
Conference24th International Conference on Automation and Computing (ICAC)
JournalICAC 2018 - 2018 24th IEEE International Conference on Automation and Computing: Improving Productivity through Automation and Computing
PublisherIEEE Xplore
Digital Object Identifier (DOI)https://doi.org/10.23919/iconac.2018.8749000
Web address (URL)http://www.cacsuk.co.uk/index.php/conferences
Journal citation(Article: 8749000)
ISBN978-186220342-6
978-1-86220-341-9
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/8742895/proceeding
Output statusPublished
Publication dates
Online01 Jul 2019
14 Jun 2018
Publication process dates
Deposited05 Jun 2023
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