ROI-based fragile watermarking for medical image tamper detection

Ameen

2021

AJRCoS

Digital image authentication techniques have recently gained a lot of attention due to their importance to a large number of military and medical applications, banks, and institutions, which require a high level of security. Generally, digital images are transmitted over insecure media, such as the Internet and computer networks of various kinds. The Internet has become one of the basic pillars of life and a solution to many of the problems left by the coronavirus. As a result, images must be protected from attempts to alter their content that might affect important decision-making. An image authentication (IA) system is a solution to this difficult problem. In the previous literature, several methods have been proposed to protect the authenticity of an image. Digital image watermark is a strategy to ensure the reliability, resilience, intellectual property, and validity of multimedia documents. Digital media, such as images, audio, and video, can hide content. Watermarking of a digital image is a mechanism by which the watermark is embedded in multimedia and the image of the watermark is retrieved or identified in a multimedia entity. This paper reviews IA techniques, watermark embedding techniques, tamper detection methods and discusses the performance of the techniques, the pros and cons of each technique, and the proposed methods for improving the performance of watermark techniques.

Section: Extensive Research On Fragile Watermark As Follow;mentioning

confidence: 99%

“…But the most important DCT, DWT, and SVD technologies are used with hybrid methods for more image security. It should be noted that the robustness of data rates and imperceptibility also needs to be handled and that the optimal swap will depend on the application [43,64,[68][69][70]73].…”

Section: Assessments and Recommenda-tionsmentioning

confidence: 99%

Image Authentication Based on Watermarking Approach: Review

Ameen

2021

AJRCoS

“…(1) According to formula (4), apply the PCET with the highest order T on each significant key frame to extract its N P exact PCET moments according to formula (5). All significant frames can produce N P × M moments.…”

Section: Extraction Of Key Frame Featuresmentioning

confidence: 99%

“…How to effectively secure these data has become a concern of researchers. As an effective way to protect intellectual property, digital watermarking [5,11,13,28,18] comes into researchers' view. With the deepening of the usefulness of video in people's life, the research on video watermarking should be paid more attention [1].…”

Section: Introductionmentioning

confidence: 99%

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

Gao

Kang

Chen

2020

Multimed Tools Appl

In this paper, a robust video zero-watermarking scheme for copyright protection using a combination of convolutional neural network (CNN) and self-organizing map (SOM) in polar complex exponential transform (PCET) space is presented. The scheme is developed not only to remedy the existing problems of lacking in some performance assessments but also to enhance the robustness. It starts with extracting the content feature of each frame by CNN and then some significant frames are selected using SOM clustering and maximum entropy. Secondly, the PCET is applied to all selected frames to abstract invariant moments, and further, is scrambled by a chaotic logistic map and is reduced in dimensions by singular value decomposition (SVD). Next, a binary sequence is generated by comparing adjacent values of the obtained compact PCET moments in the previous step, and further is permuted to produce a binary matrix. Finally, a bitwise exclusive-OR operation is imposed on the binary matrix and the encrypted watermark by the chaotic map to generate a zero-watermark signal. Experimental results demonstrate that the proposed scheme has adequate equalization and distinguishability of zero-watermarks as well as strong robustness against common signal processing, geometric, compression, and inter-frame attacks. Also, compared with existing video zero-watermarking and traditional video watermarking methods, the proposed scheme exhibits superior robustness.

Computer Science &Amp; Information Technology

“…The variation of the size of the polynomial allows on one hand to increase the authentication guarantee and to strengthen the security aspect on the other hand. In another work [9], the standard CRC-32 is used to authenticate only the Region of interest of the medical image. To achieve the authentication and integrity of different types of images, we propose a novel CRC-based fragile watermarking scheme based on FP and VD decomposition of the image.…”

Section: Introductionmentioning

confidence: 99%

A Feature-based Fragile Watermarking for Tamper Detection using Voronoi Diagram Decomposition

Golea¹,

Melkemi²

2020

Self Cite

In this paper, we have proposed a novel feature-based fragile watermarking scheme for image authentication. The proposed technique extracts Feature Points (FP) by performing the Harris corner detector and used them as germs to decomposes the host image in segments using Voronoi Diagram (VD). The authentication of each segment is guaranteed by using the Cyclic Redundancy Check code (CRC). Then, the CRC encoding procedure is applied to each segment to generate the watermark. Voronoi decomposition is employed because it has a good retrieval performance compared to similar geometrical decomposition algorithms. The security aspect of our proposed method is achieved by using the public key crypto-system RSA (Rivest-Shamir-Adleman) to encrypt the FP. Experimental results demonstrate the efficiency of our approach in terms of imperceptibility, the capability of detection of alterations, the capacity of embedding, and computation time. We have also prove the impact of VD decomposition on the quality of the watermarked image compared to block decomposition. The proposed method can be applicable in the case where the tamper detection is critical and only some regions of interest must be re-transmitted if they are corrupted, like in the case of medical images. An example of the application of our approach to medical image is briefly presented.