A Robust Zero-Watermarking Algorithm for Medical Images Using Curvelet-Dct and RSA Pseudo-random Sequences

Qin, Fengming; Li, Jingbing; Li, Hui; Nawaz, Saqib Ali; Liu, Jing

doi:10.1007/978-3-030-57881-7_16

Cited by 14 publications

(17 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our algorithm can still extract complete watermark information when the rotation angle reaches 70°, as shown in Table 4. As can be seen from Figure 16c, the algorithm proposed in this paper significantly outperforms algorithms [18][19][20] and DWT-DCT in resisting the rotation attack. For the scaling attack, as can be seen from Figure 16d, algorithms [18,19] and DWT-DCT slightly outperform our algorithm.…”

Section: Algorithm Comparisonmentioning

confidence: 84%

“…Poor robustness of geometric attacks Transformation domain NSCT-schur [9] 2022 Good translation invariance Performance of rotation attack was not tested Curvelet-DCT [19] 2020 Good invisibility and robustness of conventional attacks…”

Section: Spatial Domain Lsb-dwt [10] 2022 Good Robustness Of Gaussian...mentioning

confidence: 99%

“…The multi-scale and translation invariance of NSCT is fully utilised to improve the effectiveness of translation attacks, but it cannot resist rotation attacks better. Qin et al [19] performed DCT transform on the coarse layer of Curvelet transform to extract robust feature vectors with energy concentration in the low-frequency part, and the algorithm has good robustness against conventional and geometric attacks, where the performance of X-axis shear attack is poor. Cui et al [18] proposed an algorithm for encrypting medical image watermarking based on Tetrolet transform and DCT using DFT to encrypt the original image.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

In the intricate network environment, the secure transmission of medical images faces challenges such as information leakage and malicious tampering, significantly impacting the accuracy of disease diagnoses by medical professionals. To address this problem, the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi‐stage discrete wavelet transform (DWT), Daisy descriptor, and discrete cosine transform (DCT). The algorithm initially encrypts the original medical image through DWT‐DCT and Logistic mapping. Subsequently, a 3‐stage DWT transformation is applied to the encrypted medical image, with the centre point of the LL3 sub‐band within its low‐frequency component serving as the sampling point. The Daisy descriptor matrix for this point is then computed. Finally, a DCT transformation is performed on the Daisy descriptor matrix, and the low‐frequency portion is processed using the perceptual hashing algorithm to generate a 32‐bit binary feature vector for the medical image. This scheme utilises cryptographic knowledge and zero‐watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image, which meets the basic requirements of medical image watermarking. The embedding and extraction of watermarks are accomplished in a mere 0.160 and 0.411s, respectively, with minimal computational overhead. Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks, with a notable performance in resisting rotation attacks.

show abstract

Section: Algorithm Comparisonmentioning

confidence: 84%

Section: Spatial Domain Lsb-dwt [10] 2022 Good Robustness Of Gaussian...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Yuan,

Li,

Liu

et al. 2024

CAAI Trans on Intel Tech

View full text Add to dashboard Cite

show abstract

“…Xiyao Liu et al [79] addressed a multi-slice feature zero-watermarking scheme to improve robustness and distinguishability for medical imaging based on ring statistics and logistic-logistic system based chaotic map to guarantee distinguishability, robustness, and security the scheme results demonstrate that the proposed scheme satisfies the lossless quality requirement and robust against different attacks. Qin et al [80] proposed a new zero-watermarking methodology for medical image security. Firstly, the feature vector is constructed based on extracted features using Curvelet-DCT; then, the watermark is encrypted using a pseudo-random sequence.…”

Section:  Traditional Techniquesmentioning

confidence: 99%

A Survey on Image Data Hiding Techniques**

Mahmoud

Ghoniemy²,

Ghali³

2022

IJICIS

View full text Add to dashboard Cite

Due to the observed growth in recent years of digital image communication, computer technologies, and image processing techniques image security has been an essential demand due to the different image attacks. Image security approaches are classified into cryptography and data hiding techniques, including digital watermarking and steganography.This study paper reviews existing picture data hiding techniques, their benefits and drawbacks, and future research directions. In addition to the survey, we included a brief explanation of several geometric and image processing attacks that impair picture transmission. General multimedia security ideas, primary requirements, and recent applications We addressed various approaches and their characteristics, types, requirements, and working mechanisms. We classify the techniques based on different domains. General concepts of data hiding approaches, their characteristics, recent applications used in, also recent research work for proposed techniques is discussed in the following sections, finally, a comparison between different methodologies has been presented in a table.

show abstract

“…While realizing protection, the robust zerowatermarking takes into account the robustness and capacity of the watermarking and will not destroy the integrity of the medical image. erefore, it is very suitable for the medical image [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Zero-Watermarking Algorithm for Medical Image Based on VGG19 Deep Convolution Neural Network

Han

Jia

et al. 2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

Aiming at the security issues in the storage and transmission of medical images in the medical information system, combined with the special requirements of medical images for the protection of lesion areas, this paper proposes a robust zero-watermarking algorithm for medical images’ security based on VGG19. First, the pretrained VGG19 is used to extract deep feature maps of medical images, which are fused into the feature image. Second, the feature image is transformed by Fourier transform, and low-frequency coefficients of the Fourier transform are selected to construct the feature matrix of the medical image. Then, based on the low-frequency part of the feature matrix of the medical image, the mean-perceptual hashing algorithm is used to achieve a set of 64-bit binary perceptual hashing values, which can effectively resist local nonlinear geometric attacks. Finally, the algorithm adopts a watermarking image after scrambling and the 64-bit binary perceptual hashing value to obtain robust zero-watermarking. At the same time, the proposed algorithm utilizes Hermite chaotic neural network to scramble the watermarking image for secondary protection, which enhances the security of the algorithm. Compared with the existing related works, the proposed algorithm is simple to implement and can effectively resist local nonlinear geometric attacks, with good robustness, security, and invisibility.

show abstract

A Robust Zero-Watermarking Algorithm for Medical Images Using Curvelet-Dct and RSA Pseudo-random Sequences

Cited by 14 publications

References 17 publications

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

Robust zero‐watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

A Survey on Image Data Hiding Techniques**

Zero-Watermarking Algorithm for Medical Image Based on VGG19 Deep Convolution Neural Network

Contact Info

Product

Resources

About