An improved SVD-based watermarking technique for copyright protection

Run, Ray-Shine; Horng, Shi–Jinn; Lai, Jui-Lin; Kao, Tzong-Wang; Chen, Rong-Jian

doi:10.1016/j.eswa.2011.07.059

Cited by 182 publications

(67 citation statements)

References 10 publications

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“…Digital watermarking has become an important means of copyright protection and integrity testing, which is widely used in protection of digital image, intellectual property protection of digital work and other applications [9][10][11]. Digital watermarking algorithm has many classification methods.…”

Section: Introductionmentioning

confidence: 99%

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

Han

2016

Cybernetics and Information Technologies

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Section: Introductionmentioning

confidence: 99%

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

Han

2016

Cybernetics and Information Technologies

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“…In this study, reliability was measured as the bit error rate (BER) of extracted watermark through this formula: (14) Where, B is the number of erroneously detected bits, and is the extracted watermark image dimensions. The PSNR for the watermarked image is 46.44 dB, and the BER of the extracted watermark is zero.…”

Section: Evaluation Of the Effectivenessmentioning

confidence: 99%

“…The SVD was introduced by Eckart and Young [13] and has become one of the most widely used techniques of computational algebra and multivariate statistical analysis applied for data approximation, reduction and visualization. The use of singular value decomposition (SVD) in digital image watermarking has been widely studied [14][15].…”

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confidence: 99%

A Chaotic Blind Digital Image Watermarking Based On Singular Value Decomposition In Spatial Domain

Khorrami¹,

Ayubi²,

Behnia³

et al. 2014

J. Math. Computer Sci.

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In this letter a new watermarking scheme for Gray scale image is proposed based on a family of the chaotic maps and Singular Value Decomposition. Jacobian elliptic map is used to encrypt the watermark logo to improve the security of watermarked image. Quantum map is also used to determine the location of image's block for the watermark embedding. To test the robustness and effectiveness of our proposed method, several attacks are applied to the watermarked image and the best results have been reported. The purpose of this algorithm is to improve the shortcoming of watermarking such as small key space and low security. The experimental results demonstrate that the key space is large enough to resist the attack and the distribution of grey values of the encrypted image has a random-like behavior, which makes it a potential candidate for encryption of multimedia data such as images, audios and even videos.

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“…These methods generally are lessrobust to image and signal processing attacks and requiredlow computational efforts, while frequency domain methodstransform the representation of spatial domain into thefrequency domain and then modify its frequency coefficientsto embed the watermark.There are many transform domainwatermarking techniques such as discrete cosine transforms(DCT) [12], discrete Fourier transforms (DFT) [13][14],discrete wavelet transforms (DWT) [15][16][17], and singularvalue decomposition (SVD) [2,[18][19][20]. These methods typicallyprovide higher image imperceptibility and are muchmore robust to image manipulations, but the computationalcost is higher than spatial domain watermarking methods.The performance of watermarking methods was furtherimproved by combining two or more transformations [21][22][23][24][25][26][27][28][29][30][31][32][33].The singular value decomposition (SVD) is extensivelyused in image watermarking field in recent years due toits features. However, various researchers pointed out thefalse positive detection problem in most of the SVD-based algorithms [7,[34][35].…”

mentioning

confidence: 99%

“…Therefore, it embeds the principal component,multiplication of left singular vector matrix and the singularvalue matrix, of watermark into the host image instead ofsingular values of the watermark. On the same concept,Run et al [33] introduced an image watermarking scheme embedding the principal component of the watermark infrequency domain (DCT and DWT domains, resp.). Also,an optimization technique is applied to get the optimalscaling factors for embedding.…”

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confidence: 99%

A Normalized SVD based Image Watermarking with an Enhanced Robustness and Imperceptibility

R¹,

P²

2017

IJET

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Digital Image watermarking is one of the most active and challenging subjects in the information hiding research because it is an efficient solution to protect the copyright of the digital media. This paper proposes a new robust watermarking approach based on the selection of singular features of host image into which the watermark has to embed. The host image initially subjected to a normalization process to find the invariant features and then the obtained invariant features are subjected to Integer Wavelet Transform ( I. INTRODUCTION Digital Image Watermarking [1,2] is the process of insertion of image watermark in media content and its extraction, ifrequired, for authentication or ownership verification ofmedia content. A digital image watermark is a piece of informationthat is hidden directly in media content, in such a way thatit is imperceptible to a human observer [3]. Different types of watermarkingmethods for digital contents have been developed thatare classified into different categories depending upon theuse and the requirement of information required for theextraction/detection of watermark. To check the authenticityof a digital content fragile watermarking is used while, forthe purpose of copyright protection, robust watermarking isutilized. This classification is application-dependent. Basedon the information required for the extraction/detectionprocess watermarking schemes can be classified into blind,semi-blind, and non-blind categories. Also, one more categorizationis possible depending upon the domain of embeddingof watermark: spatial and frequency. A detailed reviewof watermarking schemes can be found in [4,5]. In digital image watermarking, there will be a common problem rises at embedding phase. i.e., the optimization of embedding constant. This constant varies from image to image and also varies based on environments. Hence there is a need to optimize embedding constant such that the watermarked image must be robust and imperceptible to any type of environments. Generally, the artificial intelligence techniques such as Genetic algorithm (GA), Particle swarm optimization (PSO), Ant colony optimization (ACO) etc., techniques will be used for optimization purposes. In [6], a novel watermarking approach was proposed by combining the both GA and PSO to obtain an improved performance in watermarking criterion. However, [6] decomposes the image through the most popular Discrete wavelet transform (DWT) which is having main problem of information loss. Due to the down sampling process in DWT, the extracted watermark and also the host image can't recover entire information. Thus, the quality of the watermark will be reduced. In [7], a block based watermarking is proposed based on Discrete Wavelet Transform (DWT) and Singular Vale decomposition (DWT). Initially, the host image was divided into the blocks of size 8X8 and then processed for DWT. From the obtained sub bands, the approximation band was subjected to SVD. Similarly all blocks are processed and the largest singular value is sele...

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An improved SVD-based watermarking technique for copyright protection

Cited by 182 publications

References 10 publications

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

A New Zero-Watermarking Algorithm Resisting Attacks Based on Differences Hashing

A Chaotic Blind Digital Image Watermarking Based On Singular Value Decomposition In Spatial Domain

A Normalized SVD based Image Watermarking with an Enhanced Robustness and Imperceptibility

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