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

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


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.

Original languageEnglish
Title of host publicationInternet of Things
PublisherSpringer India
Number of pages17
Publication statusPublished - 1 Jan 2020

Publication series

NameInternet of Things
ISSN (Print)2199-1073
ISSN (Electronic)2199-1081


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