Digital watermarking based on neural networks for color images

Yu, Pao-Ta; Tsai, Hung-Hsu; Lin, Jyh-Shyan

doi:10.1016/s0165-1684(00)00239-5

Cited by 145 publications

(54 citation statements)

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“…The experimental results have been shown that the proposed scheme is robust against various kinds of signal processing attacks. In addition, the performance of the method proposed by Yang et al is better than other reported technique (Yu et al, 2001). Vafaei et al (2013) proposed a blind watermarking method based on DWT and feed forward neural networks (FNN).…”

Section: Related Literature On Proposed Work and Research Gapsmentioning

confidence: 98%

“…In addition, these techniques can be used as optimisation techniques to remove some round off errors when coefficients in transform domain are transformed to spatial domain. Different image watermarking techniques using neural networks have been proposed (Shi-Chun et al, 2002;Yang et al, 2010;Yu et al, 2001;Vafaei et al, 2013). For a detailed description on these approaches, interested readers may directly refer to them.…”

Section: Introductionmentioning

confidence: 99%

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Robust watermarking technique using back propagation neural network: a security protection mechanism for social applications

Zear

Singh

Kumar

2017

IJICS

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Abstract:In this paper, an algorithm for digital watermarking based on discrete wavelet transforms (DWTs) and singular value decomposition (SVD) has been proposed. In the embedding process, the host colour image is decomposed into third-level DWT. Low frequency band (LL3) is transformed by SVD. The watermark image is also transformed by SVD. The S vector of watermark information is embedded in the S component of the host image. Watermarked image is generated by inverse SVD on modified S vector and original U, V vectors followed by inverse DWT. Watermark is extracted using an extraction algorithm. In order to enhance the robustness performance of the image watermark, back propagation neural network (BPNN) is applied to the extracted watermark to reduce the effects of different noise applied on the watermarked image. Results are obtained by varying the gain factor and size of the cover and watermark image, experimental results are provided to illustrate that the proposed method is able to withstand a variety of signal processing attacks and has been found to be giving superior performance for robustness and imperceptibility compared to existing methods suggested by other authors.Keywords: image watermarking; discrete wavelet transform; DWT; singular value decomposition; SVD; back propagation neural network; BPNN; normalised correlation; NC; social applications.Reference to this paper should be made as follows: Zear, A., Singh, A.K. and Kumar, P. (2017) 'Robust watermarking technique using back propagation neural network: a security protection mechanism for social applications', Int.

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Section: Related Literature On Proposed Work and Research Gapsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Robust watermarking technique using back propagation neural network: a security protection mechanism for social applications

Zear

Singh

Kumar

2017

IJICS

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“…Several works have been proposed to improve the performance of Kutter's technique. For instance, [48] enhances the robustness of the scheme by using a computational intelligence technique to choose the features of the embedded watermark with respect to the watermarked image.…”

Section: Related Workmentioning

confidence: 99%

A modular framework for color image watermarking

2016

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Abstract. We present an algorithm for fragile watermarking of color, or multi-channel, images either in uncompressed format, in lossless compressed format, or in compressed format with locally compressed units (like JPEG). The watermark is embedded into the Karhunen-Loève transform (KLT) coefficients of the host image, and the security of the method is based on the secrecy of the KLT basis computed from a corresponding secret key image. The watermark bits may be embedded with various methods, in particular the use of syndrome coding has proven flexible and effective.Genetic Algorithms (GAs) are used to find the optimum pixel modification leading to the watermark embedding. The resulting watermarked images have shown to have both a high objective quality (in terms of PSNR and SSIM) and a high subjective quality (tested by a group of observers). At the same time, the watermark extraction is very sensitive to small (±1 intensity level for single pixel) modifications, ensuring image authentication with very high probability.

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“…P.-T. Yu et al [15] proposed a novel digital watermarking technique based on neural networks for color images. The proposed technique hides an invisible watermark into a color image and then uses a neural network to learn the relationship between the embedded watermark and the watermarked image.…”

Section: Figure 2: (A) Lena Image (B) Baboon Imagementioning

confidence: 99%

A Study on Digital Image and Video Watermarking Schemes using Neural Networks

Isac¹,

Santhi²

2011

IJCA

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The use of computer network communication makes information exchange and transmission relatively simple and quick. But with digital image, audio and video products like multimedia, copyright protected security questions will be exposed in such communication environments. Digital watermarks have been recently proposed for authentication of both video and still images. This paper gives a review of a few of the proposed image and video watermarking techniques using neural networks.

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Digital watermarking based on neural networks for color images

Cited by 145 publications

References 5 publications

Robust watermarking technique using back propagation neural network: a security protection mechanism for social applications

Robust watermarking technique using back propagation neural network: a security protection mechanism for social applications

A modular framework for color image watermarking

A Study on Digital Image and Video Watermarking Schemes using Neural Networks

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