An efficient medical image watermarking scheme based on FDCuT–DCT

Thanki, Rohit M.; Borra, Surekha; Dwivedi, Ved Vyas; Borisagar, Komal R.

doi:10.1016/j.jestch.2017.06.001

Cited by 79 publications

(65 citation statements)

References 15 publications

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“…We compared the average NC values of the watermarks using our proposed algorithm under different attacks with Aditi Zear et al [18], Rohit Thanki et al [19], Xiaochen Yuan et al [21] and Amit Kumar Singh et al [22]. It can be clearly seen from Figure 23 and Table 11 that under conventional attacks, the NC values of the proposed algorithm are significantly higher than the those of the other four algorithms.…”

Section: Algorithms Comparisonmentioning

confidence: 97%

“…And under cropping attacks, left translation attacks and down translation attacks, our algorithm has obvious advantages over other algorithms in terms of NC values. Figure 24 illustrates that compared with the multi-watermarking scheme based on FDCuT-DCT proposed by Rohit Thanki et al [19], the proposed algorithm performs slightly worse in rotation (clockwise) attacks. But their NC values are not much different and performance in other geometric attacks was significantly better than the latter.…”

Section: Algorithms Comparisonmentioning

confidence: 99%

“…As the currently international compression standard, JPEG compression is widely used in watermarking [1,2,[7][8][9]. In the watermarking field, many scholars used JPEG attacks [8][9][10]13,14,18,19,21,22]. High-intensity JPEG compression may be applied to watermarking images.…”

Section: Gaussian Noise Attacksmentioning

confidence: 99%

“…(3) The final category is based on classical conventional digital watermarking. In the literature [18][19][20][21][22], an algorithm of multiple watermarks for medical images is implemented. As Aditi Zear et al [18] used SVD, DCT, DWT respectively for different type of watermarks, and back propagation neural networks (BPNN) to eliminate the impact of noise when extracting watermarks; they also enhanced its security by using Arnold transform; Rohit Thanki et al [19] used fast discrete curvelet transform (FDCuT) for medical images to obtain the different frequency coefficients of the curve decomposition, and adopted DCT for high frequency coefficients.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Liu

et al. 2019

Applied Sciences

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To resolve the contradiction between existing watermarking methods—which are not compatible with the watermark’s ability to resist geometric attacks—and robustness, a robust multi-watermarking algorithm suitable for medical images is proposed. First, the visual feature vector of the medical image was obtained by dual-tree complex wavelet transform and discrete cosine transform (DTCWT-DCT) to perform multi-watermark embedding and extraction. Then, the multi-watermark was preprocessed using the henon map chaotic encryption technology to strengthen the security of watermark information, and combined with the concept of zero watermark to make the watermark able to resist both conventional and geometric attacks. Experimental results show that the proposed algorithm can effectively extract watermark information; it implements zero watermarking and blind extraction. Compared with existing watermark technology, it has good performance in terms of its robustness and resistance to geometric attacks and conventional attacks, especially in geometric attacks.

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Section: Algorithms Comparisonmentioning

confidence: 97%

Section: Algorithms Comparisonmentioning

confidence: 99%

Section: Gaussian Noise Attacksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Liu

et al. 2019

Applied Sciences

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show abstract

“…Watermarking ensures the protection and authentication of the identity of a person that is embedded into the host audio. Although the use of watermarking in medical images has been extensively studied [26][27][28][29][30], no significant work has been reported for medical speech signals. Only a few studies have been conducted for privacy protection using medical speech signals.…”

Section: Introductionmentioning

confidence: 99%

Chaos-based robust method of zero-watermarking for medical signals

Ali

Imran

Alsulaiman

et al. 2018

Future Generation Computer Systems

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The growing use of wireless health data transmission via Internet of Things is significantly beneficial to the healthcare industry for optimal usage of health-related facilities. However, at the same time, the use raises concerns of privacy protection. Health-related data are private and should be suitably protected. Several pathologies, such as vocal fold disorders, indicate high risks of prevalence in individuals with voice-related occupations, such as teachers, singers, and lawyers. Approximately, one-third of the world population suffer from the voice-related problems during the life span and unauthorized access to their data can create unavoidable circumstances in their personal and professional lives. In this study, a zero-watermarking method is proposed and implemented to protect the identity of patients who suffer from vocal fold disorders. In the proposed method, an image for a patient's identity is generated and inserted into secret keys instead of a host medical signal. Consequently, imperceptibility is naturally achieved. The locations for the insertion of the watermark are determined by a computation of local binary patterns from the timefrequency spectrum. The spectrum is calculated for low frequencies such that it may not be affected by noise attacks. The experimental results suggest that the proposed method has good performance and robustness against noise, and it is reliable in the recovery of an individual's identity.

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Application of discrete transforms with selective coefficients for blind image watermarking

Lydia

Raj

Selvam³

et al. 2019

Trans Emerging Tel Tech

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Watermarking scheme is not helpful in conveying the original image continually so as identifying the owner's mark from the watermarked image. In the current situation, our chosen topic is significant in real‐time applications like fraud recognition, emergency clinic, and government divisions. In this study, an optimal multiblind watermarking model is proposed for the watermark detection process. Our proposed model is a combination of intelligent domain transforms like Discrete Shearlet Transform and Discrete Curvelet Transform (DCurT). The imperceptibility necessity of the plan is accomplished utilizing optimal coefficients that are performed by applying in DCurT with metaheuristic optimization model that is Grasshopper Algorithm. It is played by a chasing behavior of gathering of grasshoppers and cooperation process, here, Random Grasshopper Optimization is utilized for watermarking. The secret image is embedded with a lower band of optimal coefficients with DCurT, and here, the band is DCur (1, 5). The secret data is embedded in the host images to make it secure, and then, the extraction of the embedding process takes place inversely. For experimentation analysis, 20 digital images are considered, and different attacks are applied in the proposed watermarking model. Thus, the watermarked image looks lossless compared with the host image. Moreover, recent literary works and domain transform are also utilized for strength investigation of the proposed watermarking model.

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An efficient medical image watermarking scheme based on FDCuT–DCT

Cited by 79 publications

References 15 publications

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

A Robust Multi-Watermarking Algorithm for Medical Images Based on DTCWT-DCT and Henon Map

Chaos-based robust method of zero-watermarking for medical signals

Application of discrete transforms with selective coefficients for blind image watermarking

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