Rightful ownership through image adaptive DWT-SVD watermarking algorithm and perceptual tweaking

Pandey, Prateek; Kumar, Shishir; Singh, Satish Kumar

doi:10.1007/s11042-013-1375-2

Cited by 27 publications

(13 citation statements)

References 33 publications

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“…Recently, researchers have been working on integrating watermarking techniques based on wavelet transform coefficients and SVD to improve the robustness of watermarked images against non-geometric and geometric attacks [14], [15], [24], [27], [41], [50], [54]. Furthermore, hybrid schemes that combine these transforms with SVD are very successful in recent years [24], [37], [41].…”

Section: Related Workmentioning

confidence: 99%

“…Compared with traditional image processing techniques, even geometric distortion, the SVD-based scheme shows better strength and robustness. However, watermark embedding using the SVD technique can lead to ambiguity in the false-positive problem (FPP) [32], [45], [50], [51]. An intruder could freely get the right secret information from an illegal image, which is taken from the web or a publicly accessible source.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, researchers are also proposing watermark schemes within the frequency domain. The frequency-domain based algorithms has different applications, such as watermarking algorithms developed using frequency-domain operations like discrete wavelet transform (DWT) [1], [5], [13], [17], [24], [48], [50]. The frequency-domain of the cover data is originally broken down into different frequencies.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

2020

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Image watermarking is a robust solution for solving key issues like copyright protection and proof of ownership of digital data. Existing schemes of image watermarking mostly used grayscale or binary images as embedded watermarks, while only a few watermarking schemes are developed for color images. In this paper, we propose a novel robust semi-blind image watermarking scheme based on finite ridgelet transform (FRT), discrete wavelet transform (DWT), singular value decomposition (SVD), particle swarm optimization (PSO), and Arnold transform to protect copyright and verify the authenticity of color images. Firstly, the color image is converted from RGB to YCbCr color space, and the luminance component (Y) is taken into account to insert the watermark data. In this study, the principal component (PC) of the watermark image is directly inserted into the corresponding singular value of the cover image by the scaling factor to avoid the false positive problem (FPP). To further improve security, Arnold transform is applied to process the Y channel of the watermark image before inserting it in the cover image. Besides, PSO optimizes the embedding factor matrices. The qualitative evaluation factors like peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used to assess the visual quality, while normalized correlation coefficient (NCC) is used to assess the resemblance between the watermarked and the restored watermarked images. The performance of the proposed scheme is evaluated using geometric, non-geometric, and combinational attacks, and its comparison is performed with different image watermarking schemes to prove its robustness.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

2020

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“…Additionally particle swarm optimization has been utilized to optimize the scheme. [12] recently presented a non-blind, adaptive watermarking scheme, based on DWT and SVD, where they used principle components and perceptual tuning. [13] used a family of chaotic maps and SVD.…”

Section: Introductionmentioning

confidence: 99%

Reliable SVD based Semi-blind and Invisible Watermarking Schemes

Moulick¹,

Arora²,

Jain³

et al. 2016

IJCA

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A semi-blind watermarking scheme is presented based on Singular Value Decomposition (SVD), which makes essential use of the fact that, the SVD subspace preserves significant amount of information of an image and is a one way decomposition. The principal components are used, along with the corresponding singular vectors of the watermark image to watermark the target image. For further security, the semi-blind scheme is extended to an invisible hash based watermarking scheme. The hash based scheme commits a watermark with a key such that, it is incoherent with the actual watermark, and can only be extracted using the key. Its security is analyzed in the random oracle model and shown to be unforgeable, invisible and satisfying the property of non-repudiation.

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“…The frequency domain algorithms are resistant to filtering and compressions attacks and are generally, rotation, translation and scale invariant. Discrete Cosine Transform (DCT) [15][16][17][18] and Discrete Wavelet Transform (DWT) [19][20][21][22][23] are commonly used frequency domain techniques. Our system can be used for identifying the pirate person due to the payload that has been embedded consist the time stamp of video playback, so the suspect list can be limited.…”

Section: Introductionmentioning

confidence: 99%