Medical Image Watermarking in Four Levels Decomposition of DWT Using Multiple Wavelets in IoT Emergence

Tamara K. Al-Shayea , Constandinos X. Mavromoustakis , Jordi Mongay Batalla , George Mastorakis , Evangelos Pallis , Evangelos K. Markakis , Spyros Panagiotakis , Imran Khan

Abstract

Medical images will be an inseparable part for evaluating medical conditions of a person in real-time. This process will become efficient by exploiting the characteristics that are offered by IoT in the healthcare sectoral issues. This will allow more efficiency in the processing of a medical image. However, the medical images are exposed to the major risks through frequent attacks which may lead up to misinformation the physician in the diagnosis of the disease. Piracy eradication remains the major challenge in the present-day world in IoT platform. Subsequently, the medical watermarked image is significant technique of ensuring the clinical information that exists in the medical images. In this regard, this paper labors on a medical image based on digital watermarking can be utilized to protect health sign embedding in a medical image within an invisible status. The proposed method performance is evaluated by utilizing MSE, PSNR, SSIM, and NC, which are necessary to get the best result for performance metrics. This work is achieved in four levels Discrete Wavelet Transform (DWT). Each level is utilized different wavelet family. These wavelets family are composed of biorthogonal wavelet, reverse biorthogonal wavelet, discrete meyer wavelet, symlet wavelet, and coiflets wavelet transform. The proposed technique is highly robust against numerous sorts of attacks. The results refer that this proposed algorithm permits prevention at a higher level compared with other current structures and algorithms.
Author Tamara K. Al-Shayea - University of Nicosia (UNIC) [University of Nicosia (UNIC)]
Tamara K. Al-Shayea,,
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, Constandinos X. Mavromoustakis - University of Nicosia (UNIC) [University of Nicosia]
Constandinos X. Mavromoustakis,,
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, Jordi Mongay Batalla (FEIT / IT)
Jordi Mongay Batalla,,
- The Institute of Telecommunications
, George Mastorakis - Technological Educational Insitute of Crete (TEI) [Hellenic Mediterranean University]
George Mastorakis,,
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, Evangelos Pallis - Technological Educational Insitute of Crete (TEI) [Hellenic Mediterranean University]
Evangelos Pallis,,
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, Evangelos K. Markakis - [Hellenic Mediterranean University]
Evangelos K. Markakis,,
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, Spyros Panagiotakis - Technological Educational Insitute of Crete (TEI) [Hellenic Mediterranean University]
Spyros Panagiotakis,,
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, Imran Khan - University of Engineering and Technology, Peshawar
Imran Khan,,
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Pages15-31
Publication size in sheets0.8
Book Mastorakis George, Mavromoustakis Constandinos X., Mongay Batalla Jordi, Pallis Evangelos (eds.): Convergence of Artificial Intelligence and the Internet of Things, Internet of Things, 2020, Springer, ISBN 978-3-030-44906-3, [978-3-030-44907-0], 440 p., DOI:10.1007/978-3-030-44907-0
DOIDOI:10.1007/978-3-030-44907-0_2
URL https://link.springer.com/chapter/10.1007%2F978-3-030-44907-0_2
Languageen angielski
Score (nominal)20
Score sourcepublisherList
ScoreMinisterial score = 20.0, 17-09-2020, MonographChapterAuthor
Publication indicators Scopus Citations = 0
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