Robust Medical Image Watermarking Using Frequency Domain and Least Significant Bits Algorithms

Elbaşi, Ersin; Kaya, Volkan

doi:10.1109/iccse1.2018.8374221

Cited by 16 publications

(4 citation statements)

References 9 publications

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“…Experimental results showcase the system's ability to achieve up to 100% accuracy in tamper detection and localization, along with a 100% image recovery rate. Elbasi et al [9] used watermarking to embed patient data in medical MR images, employing two methods: one in the frequency domain (DWT, DCT, and DFT) and the other in the spatial domain (LSB). Experiments showed that frequency domain embedding resisted one set of attacks, while spatial domain embedding with LSB provided resilience against different attacks.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust medical image watermarking in frequency domain

Singh,

Shukla,

Kumar

et al. 2023

IJEER

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Protecting patient information in medical image watermarking poses a significant challenge, especially when traditional methods like the Arnold transform prove inadequate in ensuring security. This paper introduces a novel approach within the Discrete Wavelet Transform (DWT) domain to address this issue effectively. By employing the Advanced Encryption Standard (AES), the security and robustness of the system are greatly enhanced through the encryption of both the medical image and patient data. The encrypted medical image undergoes a 2-level DWT process, allowing the concealment of encrypted patient information while maintaining its invisibility. This proposed scheme surpasses others in experimental evaluations, as evidenced by metrics such as PSNR and NC, solidifying its position as a more secure choice for medical image watermarking. The results validate the scheme’s robustness and imperceptibility.

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Section: Literature Reviewmentioning

confidence: 99%

Robust medical image watermarking in frequency domain

Singh,

Shukla,

Kumar

et al. 2023

IJEER

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“…This set is obtained by arranging the DCT coefficients in a zig-zag scan and by extracting the first L+M coefficients; then watermark is embedded in the following M coefficients, the L coefficients are skipped to preserve perceptual invisibility. Ersin Elbasi and Volkan Kaya presented Robust Medical Image Watermarking using Frequency Domain and Least Significant Bits Algorithms [5]. Here both spatial domain (LSB) and frequency domain (DCT, DWT, DFT) watermarking techniques are used.…”

Section: Related Workmentioning

confidence: 99%

“…where each and every M i satisfies 0 ≤ M i < n. Then these blocks will be encrypted by using equation 5. C ≡ E(M) ≡ M^e (mod n) (5) h) Decryption: In this stage a given private key d and the generated cipher text C. The function of decryption is shown in equation 6. D(C) ≡ C^d (mod n) (6) Thus the encryption key is a positive integer pair (e; n).…”

Section: Rsa Encryption and Decryptionmentioning

confidence: 99%

Embedding and Extraction of Image Watermarking Based on the Discrete Wavelet Transform and Alpha Blending using RSA

S¹

2019

IJRASET

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Digital watermarking has become a promising research area to face the challenges created by the rapid growth in distribution of digital content over the iPnternet. To prevent misuse of this data, digital image watermarking techniques are very useful. Here, a new algorithm in the domain of discrete wavelet transform (DWT) is introduced and used for copyright protection. The elements of the logo watermark are embedded directly to the one-level DWT decomposed sub-bands. In addition to that, the watermark is encrypted using RSA algorithm for secure transmission of watermark. Few attacks have been conducted which shows the security of this work. The experimental runs and results of this work have shown that this proposed technique or method has the desired properties of digital image watermarking i.e. invisibility and robustness.

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“…Experimental results show that the algorithm is resilient against several attacks such as Gaussian noise, resizing, filtering, noise, and cropping. Authors in [17] proposed the least significant bits algorithm for medical image watermarking. In this work, there are two types of algorithms used; special domain and frequency domain.…”

Section: Introductionmentioning

confidence: 99%

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

Idham¹,

Alsaydia²,

Abdullah³

et al. 2023

EEJET

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The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

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Robust Medical Image Watermarking Using Frequency Domain and Least Significant Bits Algorithms

Cited by 16 publications

References 9 publications

Robust medical image watermarking in frequency domain

Robust medical image watermarking in frequency domain

Embedding and Extraction of Image Watermarking Based on the Discrete Wavelet Transform and Alpha Blending using RSA

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

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