Robust zero-watermarking algorithm for medical images based on SIFT and Bandelet-DCT

Fang, Yangxiu; Jing, Liu; Li, Jingbing; Cheng, Jieren; Hu, Jiabin; Dan, Yi; Xiao, Xinping; Bhatti, Uzair Aslam

doi:10.1007/s11042-022-12592-x

Cited by 31 publications

(19 citation statements)

References 22 publications

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“…In order to better demonstrate the strong robustness of the AKAZE‐DCT algorithm, the algorithm is compared with the KAZE‐DCT algorithm, SIFT‐DCT algorithm, PHTs‐DCT algorithm and DCT algorithm in the face of different attacks [21–23]. As shown in Table 11 and Figure 13, red represents DCT, green represents KAZE‐DCT, blue represents SIFT‐DCT, cyan represents PHTs‐DCT and black represents the AKAZE‐DCT proposed in this paper.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…In order to better demonstrate the strong robustness of the AKAZE-DCT algorithm, the algorithm is compared with the KAZE-DCT algorithm, SIFT-DCT algorithm, PHTs-DCT algorithm and DCT algorithm in the face of different attacks [21][22][23]. As shown in Table 11 and Figure and PHTs-DCT, AKAZE-DCT shows better robustness overall, both for conventional and geometric attacks.…”

Section: Comparison With Other Algorithmsmentioning

confidence: 99%

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Robust watermarking algorithm for medical images based on accelerated‐KAZE discrete cosine transform

Chen

et al. 2022

IET Biometrics

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With the continuous progress and development in the field of Internet technology, the area of medical image processing has also developed along with it. Specially, digital watermarking technology plays an essential role in the field of medical image processing and greatly improves the security of medical image information. A medical image watermarking algorithm based on an accelerated‐KAZE discrete cosine transform (AKAZE‐DCT) is proposed to address the poor robustness of medical image watermarking algorithms to geometric attacks, which leads to low security of the information contained in medical images. First, the AKAZE‐DCT algorithm is used to extract the feature vector of the medical image and then combined with the perceptual hashing technique to obtain the feature sequence of the medical image; then, the watermarking image is encrypted with logistic chaos dislocation to get the encrypted watermarking image, which ensures the security of the watermarking information; finally, the watermarking is embedded and extracted with the zero‐watermarking technique. The experimental results show that the algorithm can effectively extract the watermark under conventional and geometric attacks, reflecting better robustness and invisibility, and has certain practicality in the medical field compared with other algorithms.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Comparison With Other Algorithmsmentioning

confidence: 99%

Robust watermarking algorithm for medical images based on accelerated‐KAZE discrete cosine transform

Chen

et al. 2022

IET Biometrics

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“…Commonly used feature descriptors are SIFT (Scale Invariant Feature Transform) [20,25,26], SURF (Speeded Up Robust Features) [22][23][24], FAST (Features from accelerated segment test) [26], Daisy [27] etc. Fang et al [20] used the SIFT algorithm to extract image features and perform bandelet transform and DCT on their characteristics to obtain the feature vector of medical images. This algorithm has good robustness but poor resistance to cropping attacks, high computational cost, and does not take into account the problem of missing pixel values resulting in missing extracted watermarks due to rotation attacks.…”

Section: Introductionmentioning

confidence: 99%

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

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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.

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“…Meng et al [29] and Liu et al [30] developed an irreversible watermarking scheme using wavelet transform and U-net based machine learning method. Fang et al [31] proposed an information hiding technique based on adversarial generative networks to effectively secure data in data sharing. Uchida et al [32] embedded watermarking information in the network model without affecting the performance of the network to ensure the intellectual property of the shared neural network model.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Watermarking Algorithm for Medical Images Using Inception V3燼nd燚CT

Yang¹,

Li²,

Bhatti³

et al. 2023

Computers, Materials &Amp; Continua

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Medical images are a critical component of the diagnostic process for clinicians. Although the quality of medical photographs is essential to the accuracy of a physician's diagnosis, they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images. Traditional watermark embedding algorithm embeds the watermark information into the medical image, which reduces the quality of the medical image and affects the physicians' judgment of patient diagnosis. In addition, watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed. This paper proposes a novel watermarking algorithm using the convolutional neural networks (CNN) Inception V3 and the discrete cosine transform (DCT) to address above mentioned problems. First, the medical image is input into the Inception V3 network, which has been structured by adjusting parameters, such as the size of the convolution kernels and the typical architecture of the convolution modules. Second, the coefficients extracted from the fully connected layer of the network are transformed by DCT to obtain the feature vector of the medical image. At last, the watermarks are encrypted using the logistic map system and hash function, and the keys are stored by a third party. The encrypted watermarks and the original image features are performed logical operations to realize the embedding of zero-watermark. In the experimental section, multiple watermarking schemes using three different types of watermarks were implemented to verify the effectiveness of the three proposed algorithms. Our NC values for all the images are more than 90% accurate which shows the robustness of the algorithm. Extensive experimental results demonstrate the robustness under both conventional and high-intensity geometric attacks of the proposed algorithm.

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Robust zero-watermarking algorithm for medical images based on SIFT and Bandelet-DCT

Cited by 31 publications

References 22 publications

Robust watermarking algorithm for medical images based on accelerated‐KAZE discrete cosine transform

Robust watermarking algorithm for medical images based on accelerated‐KAZE discrete cosine transform

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

A Multi-Watermarking Algorithm for Medical Images Using Inception V3燼nd燚CT

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