Reversible watermarking scheme for medical image based on differential evolution

Lei, Baiying; Tan, Eng Leong; Chen, Siping; Ni, Dong; Wang, Tianfu; Lei, Haijun

doi:10.1016/j.eswa.2013.11.019

Cited by 121 publications

(91 citation statements)

References 50 publications

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“…An et al 7 embedded a watermark in the wavelet domain based on shifting and clustering of statistical histograms. Lei et al 8 embedded the signature information and textual data into DWT-SVD domain of medical images based on recursive dither modulation (RDM). These reversible watermarking schemes can recover medical images losslessly after watermark extraction and their embedded watermark is hardly to be removed, which is superior to ROI lossless watermarking schemes.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, robust reversible watermarking schemes [6][7][8] have been proposed to protect medical images. An et al 6 proposed a content-adaptive reversible watermarking scheme based on histogram rotation technique.…”

Section: Introductionmentioning

confidence: 99%

“…The existing watermarking schemes for medical images can be classified into three main categories: the regions of interest (ROI) lossless watermarking [1][2][3][4][5] , reversible watermarking [6][7][8] and zero-watermarking [9][10][11] . All of them use the information for authentication or copyright identification as watermark.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

Liu

Lou

Wang

et al. 2018

Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

Liu

Lou

Wang

et al. 2018

Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

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“…Furthermore, there exist certain applications such as military communication, healthcare, and law-enforcement that may not accept even small quality degradation of cover media prior to the downstream processing. In such cases, reversible data hiding schemes [32,52,56] are employed instead of conventional data hiding schemes. Reversible data hiding of digital content allows full extraction of the hidden data along with the complete restoration of the cover media.…”

Section: Introductionmentioning

confidence: 99%

“…Data hiding is the art and science for embedding data into cover media such as audio, video, or image to build a covert channel for secret communication, for the purpose of verifying the integrity, for the copyright protection, or for other purpose [21,31,34,43,50,52,56,70,72,75,78,107,115,122]. Data hiding schemes can be categorized into two groups: watermarking and steganography [17,92].…”

Section: Introductionmentioning

confidence: 99%

Data Hiding Schemes: A Survey

Ali¹,

Ahn²,

Pant³

2016

Gate to Computer Science and Research

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Data hiding is the process of hiding an amount of data, called secret message or watermark, into a cover media that may be audio, video, or image signal, in an imperceptible way for different purposes. Due to the advances in generation, storage, and communication technology of digital media, the necessity and importance of data hiding has drawn the attention of many researchers all over the world resulting in a lot of variants of data hiding scheme. This chapter provides a detailed review of the basic concepts of data hiding and a survey of its major variants developed so far. The chapter classifies the data hiding schemes based on several aspects of data hiding comprising artificial intelligence. Furthermore, the chapter also provides the recommendations to the interested users for further research. This review may be a useful insight and a good source for the users who are interested in the application of artificial intelligence in data hiding.

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NSCT domain–based secure multiple‐watermarking technique through lightweight encryption for medical images

Thakur

Singh

Ghrera

2018

Concurrency and Computation

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This paper discusses a lightweight encryption-based secure digital watermarking technique for medical applications. The technique uses redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) along with nonsubsampled contourlet transform (NSCT) to improve robustness and imperceptibility. The security of the proposed technique is further improved by incorporating a lightweight (low-complexity) cryptographic mechanism that is applied after embedding multiple watermarks. The proposed scheme first partitions the host image into subcomponents and then calculates the entropy values for it. To the maximum entropy value, the NSCT is applied, followed by RDWT decomposition. Finally, SVD is applied to obtain a singular vector of RDWT-decomposed components. The watermark images are also processed using the same procedure mentioned above. The method uses singular values to hide watermarks into a host image. The experimental outcome shows that the combined technique makes our proposed approach more robust and imperceptible, while it is evaluated for various wavelet filters and 10 different types of medical and five different types of nonmedical cover images. Furthermore, the strength of the cryptographic mechanism is tested using standard performance measures and confirms its effectiveness in security. Moreover, it is evident from the results that our method shows improvement in robustness in comparison to previously reported techniques under consideration.

show abstract

Reversible watermarking scheme for medical image based on differential evolution

Cited by 121 publications

References 50 publications

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

Discriminative and robust zero-watermarking scheme based on completed local binary pattern for authentication and copyright identification of medical images

Data Hiding Schemes: A Survey

NSCT domain–based secure multiple‐watermarking technique through lightweight encryption for medical images

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