Survey on Reversible Watermarking Techniques of Echocardiography

Ghafoor, Rabiya; Saleem, Danish; Jamal, Sajjad Shaukat; Ishtiaq, Muhammad; Ejaz, Sadaf; Малик, Аднан; Khan, Muhammad Fahad

doi:10.1155/2021/8820082

Cited by 3 publications

(4 citation statements)

References 35 publications

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“…First, use the method in Section 3.2 to obtain the same chaotic sequence X(i), and similarly, use it to construct the binary matrix K(i, j). Finally, the extracted watermark EW ′ (i, j) is decrypted according to equation (8), and the unencrypted watermark W ′ (i, j) is obtained. Figure 10 shows this process.…”

Section: Watermark Decryptionmentioning

confidence: 99%

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Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Gong

Bhatti

et al. 2021

Security and Communication Networks

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To protect the patient information in medical images, this article proposes a robust watermarking algorithm for medical images based on Harris-SURF-DCT. First, the corners of the medical image are extracted using the Harris corner detection algorithm, and then, the previously extracted corners are described using the method of describing feature points in the SURF algorithm to generate the feature descriptor matrix. Then, the feature descriptor matrix is processed through the perceptual hash algorithm to obtain the feature vector of the medical image, which is a binary feature vector with a size of 32 bits. Secondly, to enhance the security of the watermark information, the logistic map algorithm is used to encrypt the watermark before embedding the watermark. Finally, with the help of cryptography knowledge, third party, and zero-watermarking technology, the algorithm can embed the watermark without modifying the medical image. When extracting the watermark, the algorithm can extract the watermark from the test image without the original image. In addition, the algorithm has strong robustness to conventional attacks and geometric attacks. Especially under geometric attacks, the algorithm performs better.

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Section: Watermark Decryptionmentioning

confidence: 99%

“…Most of the traditional medical systems have turned to electronic medical systems [7]. Patient data such as current and past disease information, medical images, and drug information can be stored in electronic medical records (EMR) [8].…”

Section: Introductionmentioning

confidence: 99%

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Gong

Bhatti

et al. 2021

Security and Communication Networks

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show abstract

“…Many algorithms have been proposed in the literature and often rely on robust random key generation [13]. A method of generating a secure key with reduced latency and based on the cardiogram in encryption [14] has been proposed. An improved method was proposed by [15] to heal the medical image using Fibonacci, which had the effect of scattering and hiding the information of the medical image [16].…”

Section: Related Workmentioning

confidence: 99%

Secure medical image transmission using deep neural network in e‐health applications

Alarood

Faheem

Al‐Khasawneh

et al. 2023

Healthcare Tech Letters

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Recently, medical technologies have developed, and the diagnosis of diseases through medical images has become very important. Medical images often pass through the branches of the network from one end to the other. Hence, high-level security is required. Problems arise due to unauthorized use of data in the image. One of the methods used to secure data in the image is encryption, which is one of the most effective techniques in this field. Confusion and diffusion are the two main steps addressed here. The contribution here is the adaptation of the deep neural network by the weight that has the highest impact on the output, whether it is an intermediate output or a semi-final output in additional to a chaotic system that is not detectable using deep neural network algorithm. The colour and grayscale images were used in the proposed method by dividing the images according to the Region of Interest by the deep neural network algorithm. The algorithm was then used to generate random numbers to randomly create a chaotic system based on the replacement of columns and rows, and randomly distribute the pixels on the designated area. The proposed algorithm evaluated in several ways, and compared with the existing methods to prove the worth of the proposed method.

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“…The authors also suggested that hardware-based watermarking can be used to support real-time applications. Finally, they recommended that the hybridization of two or more watermarking techniques will enhance watermarking performance; however, this will also increase the computational complexity.Ghafoor et al[101] provided an overview of reversible watermarking in echocardiography applications. Reversible watermarking is an efficient tool which has uses in critical domains such as military and medical applications.…”

mentioning

confidence: 99%

Digital Watermarking—A Meta-Survey and Techniques for Fake News Detection

Malanowska,

Mazurczyk,

Araghi

et al. 2024

IEEE Access

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During the past few decades, research on digital media watermarking -initially designed for digital images with the envisioned applications of copyright protection or copy control-has significantly evolved with respect to other covers (i.e., video, audio, speech) and many more potential applications, including tamper detection, broadcast monitoring, and, more recently, fake news detection. As a result, various surveys have tried to summarize certain aspects of this research field as it has grown. This has led to more than 130 survey papers being written at different points in time, describing various parts of the scientific efforts focused on digital media watermarking. Considering the above, the aim of this paper is twofold. First, we conduct a meta-survey based on 64 selected research works, in order to summarize the most notable survey papers in this field, which allows us to ''draw a map'' of this research area. Second, we focus on providing the requirements for digital watermarking techniques when applied to their most recent application: detecting fake news in multimedia content. Finally, an outline of the approach taken within the DISSIMILAR (Detection of fake newS on SocIal MedIa pLAtfoRms) project for the detection of disinformation is presented.

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Survey on Reversible Watermarking Techniques of Echocardiography

Cited by 3 publications

References 35 publications

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

Secure medical image transmission using deep neural network in e‐health applications

Digital Watermarking—A Meta-Survey and Techniques for Fake News Detection

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