Open Access

ARTICLE

Robust Watermarking Scheme for NIfTI Medical Images

by Abhishek Kumar^1,5, Kamred Udham Singh², Visvam Devadoss Ambeth Kumar³, Tapan Kant⁴, Abdul Khader Jilani Saudagar^5,*, Abdullah Al Tameem⁵, Mohammed Al Khathami⁵, Muhammad Badruddin Khan⁵, Mozaherul Hoque Abul Hasanat⁵, Khalid Mahmood Malik⁶

1 School of Computer Science and IT, JAIN (Deemed to be University), Bangalore, 560069, India
2 Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, 701, Taiwan
3 Department of Computer Science & Engineering, Panimalar Engineering College, Anna University, Chennai, 600123, India
4 Patna Women's College, Patna, 800001, India
5 Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
6 Department of Computer Science and Engineering, Oakland University, Rochester, 48309, USA

* Corresponding Author: Abdul Khader Jilani Saudagar. Email:

(This article belongs to the Special Issue: Edge Computing and Machine Learning for Improving Healthcare Services)

Computers, Materials & Continua 2022, 71(2), 3107-3125. https://doi.org/10.32604/cmc.2022.022817

Received 19 August 2021; Accepted 09 October 2021; Issue published 07 December 2021

Abstract

Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI) technologies are widely used in medical field. Within the last few months, due to the increased use of CT scans, millions of patients have had their CT scans done. So, as a result, images showing the Corona Virus for diagnostic purposes were digitally transmitted over the internet. The major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the internet. As a result, it is important to apply a robust and secure watermarking technique to these images. Notably, watermarking schemes have been developed for various image formats, including .jpg, .bmp, and .png, but their impact on NIfTI (Neuroimaging Informatics Technology Initiative) images is not noteworthy. A watermarking scheme based on the Lifting Wavelet Transform (LWT) and QR factorization is presented in this paper. When LWT and QR are combined, the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme's robustness. Multiple watermarks are added to the host image in this approach. Measuring the performance of the graphics card is done by using PSNR, SSIM, Q (a formula which measures image quality), SNR, and Normalized correlation. The watermarking scheme withstands a variety of noise attacks and conversions, including image compression and decompression.

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Keywords

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