Genetic algorithm based watermarking in double-density dual-tree DWT

Kumaran, T. Vasantha; Thangavel, P.

doi:10.1109/icwapr.2008.4635847

Cited by 4 publications

(5 citation statements)

References 12 publications

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“…Kumaran and Thangavel [13] proposed a technique based on the GA for optimizing the image watermarking, it was applied to the double-density dual-tree discrete wavelet transform. The proposed technique improved the robustness of the watermark and the quality of the watermarked image.…”

Section: Related Workmentioning

confidence: 99%

“…For each generation, the steps (7-44) will be executed as follows. Lines (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25) illustrate the watermark embedding process. In lines (7)(8)(9)(10)(11)(12), the host image and the watermark image are loaded, then the host image is divided into non overlapping blocks of size 8*8 and a number of Sb blocks are selected randomly for the embedding process with keeping their positions in K as a secret key to be used in the extraction process.…”

Section: Optimization Processmentioning

confidence: 99%

“…The watermark image is divided into four parts [wp 1 , wp 2 , wp 3 , wp 4 ], in which each part will be embedded in its corresponding wavelet sub-band. In lines (13)(14)(15)(16)(17)(18)(19)(20)(21)(22), each selected block is decomposed into its multiresolution representation using second level DWT, then four sub-bands are selected to embed the watermark, which are (HH 21 , LL 22 , HH 23 , LL 24 ). WHT is applied on each sub-band and the watermark bit is embedded in the WHT first coefficient using the generated GA scaling factors.…”

Section: Optimization Processmentioning

confidence: 99%

“…Artificial intelligence (AI) techniques like fuzzy logic, genetic algorithm, and neural networks can be used to solve the optimization problems [1,13]. Recently, many researchers started to use Machine Learning Techniques (MLTs) for digital watermarking to adjust the frequency coefficients with adaptive methods [36].…”

Section: Introductionmentioning

confidence: 99%

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Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Houby

Yassin

2020

Multimed Tools Appl

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Recently the active use of Internet and multimedia technologies has increased the violation of copyright. Digital watermarking has a crucial role in the field of multimedia copyright protection. In this paper, an optimized image watermarking technique based on Discrete Wavelet Transform (DWT) and Hadamard transform is proposed. Genetic Algorithm (GA) is an optimizing technique used to satisfy the tradeoff between robustness and imperceptibility. Blind property is conducted using the estimation capability of Decision Tree (DT). First the host image is transformed using second level DWT, then Hadamard transform is applied on selected DWT sub-bands. Adaptive multiple strength values are computed using GA. The watermark is successfully extracted using the trained DT which estimates the original coefficients needed for the extraction process without the need for the original host image. The proposed technique is evaluated against several types of attacks: compression, median filtering, salt and pepper noise, histogram equalization, blurring, scaling, painting, and cropping. Experimental results show that the proposed watermarking technique is robust against these attacks while keeping good imperceptibility. The proposed technique outperforms the compared techniques according to robustness, imperceptibility, and capacity.

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Section: Related Workmentioning

confidence: 99%

Section: Optimization Processmentioning

confidence: 99%

Section: Optimization Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Houby

Yassin

2020

Multimed Tools Appl

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“…employ scene-segmentation together with a 3D CWT for video watermarking Coria et al (2008). embed a spread-spectrum watermark in the coarse subbands and correlate over multiple frames of a video sequence to achieve robustness against geometrical distortions Kumaran and Thangavel (2008). turn to the recently proposed double-density dual-tree DWT domain (Selesnick, 2004) and investigate two quantizationbased embedding strategies with genetic optimization.…”

mentioning

confidence: 99%

Blind Detection of Additive Spread-Spectrum Watermarking in the Dual-Tree Complex Wavelet Transform Domain

Kwitt

Meerwald

Uhl

2010

International Journal of Digital Crime and Forensics

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In this paper, the authors adapt two blind detector structures for additive spread-spectrum image watermarking to the host signal characteristics of the Dual-Tree Complex Wavelet Transform (DT-CWT) domain coefficients. The research is motivated by the superior perceptual characteristics of the DT-CWT and its active use in watermarking. To improve the numerous existing watermarking schemes in which the host signal is modeled by a Gaussian distribution, the authors show that the Generalized Gaussian nature of Dual-Tree detail subband statistics can be exploited for better detector performance. This paper finds that the Rao detector is more practical than the likelihood-ratio test for their detection problem. The authors experimentally investigate the robustness of the proposed detectors under JPEG and JPEG2000 attacks and assess the perceptual quality of the watermarked images. The results demonstrate that their alterations allow significantly better blind watermark detection performance in the DT-CWT domain than the widely used linear-correlation detector. As only the detection side has to be modified, the proposed methods can be easily adopted in existing DT-CWT watermarking schemes.

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A Multimedia Watermark scheme based on double density dual-Tree discrete wavelet transform and singular value decomposition

Agoyi¹,

Seral²

2012

2012 20th Signal Processing and Communications Applications Conference (SIU)

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Genetic algorithm based watermarking in double-density dual-tree DWT

Cited by 4 publications

References 12 publications

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Blind Detection of Additive Spread-Spectrum Watermarking in the Dual-Tree Complex Wavelet Transform Domain

A Multimedia Watermark scheme based on double density dual-Tree discrete wavelet transform and singular value decomposition

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