An efficient and secure robust watermarking scheme for document images using Integer wavelets and block coding of binary watermarks

Chetan, K. R.; Nirmala, S. Jaya

doi:10.1016/j.jisa.2015.07.002

Cited by 22 publications

(9 citation statements)

References 23 publications

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“…wk=decimal(l bit secret data) (11) wk C C   ' (12) Finally, inverse integer wavelet transform is applied to generate a watermarked medical image (W). It is transmitted to the remote specialists.…”

Section: Proposed Systemmentioning

confidence: 99%

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Medical Image Watermarking Technique Using Image Interpolation in Transform Domain

Shanmugapriya¹,

Santhi²,

Mohan³

2018

IJET

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In telemedicine, medical data are shared across the world among different specialists for various purposes through an unsecured medium. So there is a need to protect the medical data during transmission. With the help of image watermarking techniques, medical images are protected along with the electronic patient information (EPI). This paper proposes a medical image watermarking, by applying wavelet transform, using an interpolation technique. EPI data is embedded within the transformed medical image to generate a watermarked image. At the extraction side, EPI data are extracted and medical image is reconstructed without any loss. The performance of the proposed method is analyzed using a peak signal to noise ratio (PSNR), mean absolute error (MAE) and structural similarity index (SSIM). The experimental result shows that the proposed method gives better results.

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Section: Proposed Systemmentioning

confidence: 99%

“…Using the singular value decomposition (SVD) watermark is embedded within a subband. Chetan and Nirmala [12] implemented robust image watermarking using integer wavelet transform (IWT). The watermark is coded using block level coding and embedded within a wavelet sub band of the image.…”

Section: Introductionmentioning

confidence: 99%

Medical Image Watermarking Technique Using Image Interpolation in Transform Domain

Shanmugapriya¹,

Santhi²,

Mohan³

2018

IJET

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“…Several algorithms have been proposed in the literature to create robust and imperceptible watermarks. In general, watermarking methods can be divided into three main categories: (i) blind methods [1][2][3][4][5][6][7][8][9][10][11][12][13], (ii) semi-blind methods [14][15][16][17] (iii) non-blind methods [18][19][20][21][22][23][24]. A blind watermarking framework for high dynamic range images (HDRIs) is proposed in [1].…”

Section: Introductionmentioning

confidence: 99%

SVD-Based Image Watermarking Using the Fast Walsh-Hadamard Transform, Key Mapping, and Coefficient Ordering for Ownership Protection

et al. 2019

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Proof of ownership on multimedia data exposes users to significant threats due to a myriad of transmission channel attacks over distributed computing infrastructures. In order to address this problem, in this paper, an efficient blind symmetric image watermarking method using singular value decomposition (SVD) and the fast Walsh-Hadamard transform (FWHT) is proposed for ownership protection. Initially, Gaussian mapping is used to scramble the watermark image and secure the system against unauthorized detection. Then, FWHT with coefficient ordering is applied to the cover image. To make the embedding process robust and secure against severe attacks, two unique keys are generated from the singular values of the FWHT blocks of the cover image, which are kept by the owner only. Finally, the generated keys are used to extract the watermark and verify the ownership. The simulation result demonstrates that our proposed scheme is highly robust against numerous attacks. Furthermore, comparative analysis corroborates its superiority among other state-of-the-art methods. The NC of the proposed method is numerically one, and the PSNR resides from 49.78 to 52.64. In contrast, the NC of the state-of-the-art methods varies from 0.7991 to 0.9999, while the PSNR exists in the range between 39.4428 and 54.2599.

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“…Image watermarking based on transformed-domain produces a good robustness against several attacks. The transformed-domains such as Discrete Cosine Transform (DCT) [2]- [5], Discrete Wavelet Transform (DWT) [6], [7], Integer Wavelet Transform (IWT) [8] have been widely used in image watermarking schemes.…”

Section: Introductionmentioning

confidence: 99%

Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

Ernawan

Ariatmanto

2019

IJECE

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With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8×8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack.

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An efficient and secure robust watermarking scheme for document images using Integer wavelets and block coding of binary watermarks

Cited by 22 publications

References 23 publications

Medical Image Watermarking Technique Using Image Interpolation in Transform Domain

Medical Image Watermarking Technique Using Image Interpolation in Transform Domain

SVD-Based Image Watermarking Using the Fast Walsh-Hadamard Transform, Key Mapping, and Coefficient Ordering for Ownership Protection

Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

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