Blind image watermarking technique based on differential embedding in DWT and DCT domains

Benoraira, Ali; Benmahammed, K.; Boucenna, Noureddine

doi:10.1186/s13634-015-0239-5

Cited by 74 publications

(35 citation statements)

References 24 publications

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“…(7) Normalize cor1 and cor2 according to Equation (20). (8) Repeat steps (1) to (7) 1000 times and record the experimental results, cor1, cor2, cor3, and cor4.…”

Section: Applicability Analysismentioning

confidence: 99%

“…Moreover, the proposed detection algorithm is compatible with single watermarking detection algorithms, and it has good performance in terms of detection efficiency. Therefore, multiple watermarking technology can effectively solve the above information security problems of vector geographic data.Currently, many scholars have been devoted to developing digital watermark technology, and they have proposed many algorithms [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. However, these algorithms focus on embedding only one watermark in the cover data, which then lacks multi-copyright protection.…”

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confidence: 99%

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An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data

et al. 2018

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Vector geographic data play an important role in location information services. Digital watermarking has been widely used in protecting vector geographic data from being easily duplicated by digital forensics. Because the production and application of vector geographic data refer to many units and departments, the demand for multiple watermarking technology is increasing. However, multiple watermarking algorithm for vector geographic data draw less attention, and there are many urgent problems to be solved. Therefore, an efficient robust multiple watermark algorithm for vector geographic data is proposed in this paper. The coordinates in vector geographic data are first randomly divided into non-repetitive sets. The multiple watermarks are then embedded into the different sets. In watermark detection correlation, the Lindeberg theory is used to build a detection model and to confirm the detection threshold. Finally, experiments are made in order to demonstrate the detection algorithm, and to test its robustness against common attacks, especially against cropping attacks. The experimental results show that the proposed algorithm is robust against the deletion of vertices, addition of vertices, compression, and cropping attacks. Moreover, the proposed detection algorithm is compatible with single watermarking detection algorithms, and it has good performance in terms of detection efficiency. Therefore, multiple watermarking technology can effectively solve the above information security problems of vector geographic data.Currently, many scholars have been devoted to developing digital watermark technology, and they have proposed many algorithms [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. However, these algorithms focus on embedding only one watermark in the cover data, which then lacks multi-copyright protection. Multiple watermarking draws less attention than single watermarking, and it does not simply involve the embedding of different watermarks by using the single watermarking algorithm. The multiple watermarking algorithm commonly focuses on images and videos. There are three main methods for addressing the impact of multiple watermarks, as described in References [17][18][19][20][21][22][23][24][25][26][27][28][29][30]. The first is dividing the images into multiple blocks for multiple watermarks [17,18,27,29]. The second is embedding multiple watermarks into different frequency domains or channels [19][20][21][22][23]26,30]. The last is merging multiple watermarks into one [24,25,27]. Usually multiple methods are combined in one algorithm. In the above references, only a few previous works have been proposed for vector geographic data; for instance, References [24-29]. Sun et al. combined a child copyright watermark with another child watermark consisting of features selected by fuzzy clustering from the vector map. The new watermark was then embedded into the vector map [24]. Li et al. proposed a multiple watermark embedding solution through the generation of additional information with waterma...

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“…(7) Normalize cor1 and cor2 according to Equation (20). (8) Repeat steps (1) to (7) 1000 times and record the experimental results, cor1, cor2, cor3, and cor4.…”

Section: Applicability Analysismentioning

confidence: 99%

mentioning

confidence: 99%

An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data

et al. 2018

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“…The reason for the advanced watermarks may be will gatherings give copyright insurance for licensed innovation that's on advanced arrangement. [4] In this way watermark will be those concealed data inside the advanced indicator. There would a number requisitions for advanced watermarking Anyway Around the greater part copyright protection, substance authentication, duplicate and use control Furthermore content portrayal are imperative provision region of the advanced" watermarking.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Image Watermarking for Combination of RST Attacks

Degadwala¹,

Gaur²

2017

IJCA

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Nowadays in network communication need to protect the transmission, also right to advance networking helpful fast Communication. Therefore, networking makers need to additional consistently handling illegal use of the data. In our proposed approach, first enter the user name and password then generate QR-code using zxing library that will converted in to the share using Binary Visual cryptography algorithm. Now share-2 is save in the database that is for future reference at receiver side. Now share-1 is embedding into the RComponent LL bit using of block DWT-SVD and Pseudo Zernike moment. After embedding add G, B Component. Now Color watermark image transfer from the network. As in network there are different attackers apply combination of Rotation, Scale and Translation attacks on the color watermark image. For recover the attacks first apply Pseudo Zernike moment, Surf feature on R-component they will extract the attacks pixel and recover the scale-angle using affine transformation. Now share-1 and another share-2 is in data base so we will apply EX-OR operation to get the QRCode. The final QR-code is decoded and we get the user name and password. This research work can give a way for providing Security to Authority data and give protection against Attacks.

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“…Changes in such coefficients are not visible to human eye. Thus embedding the watermark in HH allows the watermark to be embedded without being perceived by the human eye [17].…”

Section: B Discrete Wavelet Transform (Dwt)mentioning

confidence: 99%

A Semi-Blind Watermarking of Color Images Using Slant Transform, DWT and SVD

Koju¹,

Joshi²

2017

IJIGSP

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Abstract-This paper presents a robust watermarking for still digital images based on a Slant transform, discrete wavelet transforms and Singular Value Decomposition (SVD). The cover image is transformed using discrete wavelet transform and singular value decomposition while watermark image is transformed using slant transform. It is watermarked by replacing singular values of the highfrequency and low-frequency component of an original image by that of slant transformed watermarks. Experimental results show that our method guarantees the robust resistance against no attack and the robustness against common image processing attacks such as JPEG compression, cropping, histogram equalization, sharpening etc.

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Blind image watermarking technique based on differential embedding in DWT and DCT domains

Cited by 74 publications

References 24 publications

An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data

An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data

An Efficient Image Watermarking for Combination of RST Attacks

A Semi-Blind Watermarking of Color Images Using Slant Transform, DWT and SVD

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