Robust and false positive free watermarking in IWT domain using SVD and ABC

Ansari, Irshad Ahmad; Pant, Millie; Ahn, Chang Wook

doi:10.1016/j.engappai.2015.12.004

Cited by 118 publications

(53 citation statements)

References 32 publications

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“…Due to these properties, SVD has been gradually applied in digital watermarking schemes [16][17][18]. Taking N = 4 for example, the SVD can be rewritten as …”

Section: Singular Value Decomposition (Svd)mentioning

confidence: 99%

Fragile Watermarking for Image Authentication Using the Characteristic of SVD

2017

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Digital image authentication has become a hot topic in the last few years. In this paper, a pixel-based fragile watermarking method is presented for image tamper identification and localization. By analyzing the left and right singular matrices of SVD, it is found that the matrix product between the first column of the left singular matrix and the transposition of the first column in the right singular matrix is closely related to the image texture features. Based on this characteristic, a binary watermark consisting of image texture information is generated and inserted into the least significant bit (LSB) of the original host image. To improve the security of the presented algorithm, the Arnold transform is applied twice in the watermark embedding process. Experimental results indicate that the proposed watermarking algorithm has high security and perceptual invisibility. Moreover, it can detect and locate the tampered region effectively for various malicious attacks.

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“…Due to these properties, SVD has been gradually applied in digital watermarking schemes [16][17][18]. Taking N = 4 for example, the SVD can be rewritten as …”

Section: Singular Value Decomposition (Svd)mentioning

confidence: 99%

Fragile Watermarking for Image Authentication Using the Characteristic of SVD

2017

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“…I. A. Ansari et al [19] proposed robust and false positive free watermarking scheme using LWT and SVD. The authors employed a metaheuristic optimization technique in their scheme to find the optimal value of scaling factor.…”

Section: Fig 1 a Block Diagram Of Generic Watermarking Systemmentioning

confidence: 99%

An Improved Digital Image Watermarking Scheme using Particle Swarm Optimization Technique

Takore¹

2017

IJRASET

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Digital watermarking has been proposed as most effective ways to protect a copyright of digitally formatted multimedia documents in networked environments by inserting secret data into host image without significantly affecting the visual quality. Robustness to different accidental or intentional attacks is the most desired watermarking requirements for copyright protection application. This study presents a robust, blind and an imperceptible image watermarking scheme based on lifting wavelet transforms (LWT), discrete cosine transform (DCT), singular value decomposition (SVD) and particle swarm optimization (PSO). Block-based DCT and SVD are performed on reference sub-images which are formed by taking alternative pixels across row and column. A binary watermark is embedded in the first reference sub-image by modifying singular values and the other sub-image is used as a reference for both watermarks embedding and extracting. Different standard grayscale images have been used as test images and the obtained experimental results show improvement in both imperceptibly and robustness against various attacks.

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“…Frequency domain algorithms provide an alternative for this issue and hence the watermarking schemes based on DCT [8], DWT, RDWT [9,10] and SVD [11] have gained momentum in watermarking concepts. SVD combined with transforms such as DCT, DWT, RDWT are more efficient than SVD based methods [12]. DWT-SVD based watermarking schemes provide better robustness and imperceptibility [13] because of the sensitiveness to modeling of DWT.…”

Section: Introductionmentioning

confidence: 99%

“…Transform coefficients of the host image are modified in accordance to the watermark image coefficients as per the watermarking criteria [12] Less robustness and imperceptibility against various attacks [16] Better robustness and imperceptibility [5,17] Less complex [18,19] Complexity based on the type of the transform Even distribution of watermark values in the host image Watermark values are distributed all over the host image because of the inverse transform [20] These robust methods are very much useful for the protection of copyrights and ownership authentication.…”

Section: Introductionmentioning

confidence: 99%

Linear weighted watermarking using normalized principal components

Sangeetha¹,

Anita²

2017

Complex Intell. Syst.

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This manuscript introduces a novel linear weighted watermarking through normalized principal components using discrete wavelet transform (DWT) and singular value decomposition (SVD). Weight evaluation for embedding a singular value matrix of a watermark into a host is a trivial task in watermark embedding process. This task is accomplished by the normalized principal components derived from the singular value matrices of HH subbands of the host and the watermark images. Experiments are conducted to analyze the effectiveness of the proposed watermark embedding and watermark-host extraction processes against the other DWT-SVD based watermarking schemes. Performance of this method is analyzed by peak signal to noise ratio, structural similarity index and correlation coefficient. The proposed method is also tested against various geometrical and non-geometrical attacks on watermarked images.

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Robust and false positive free watermarking in IWT domain using SVD and ABC

Cited by 118 publications

References 32 publications

Fragile Watermarking for Image Authentication Using the Characteristic of SVD

Fragile Watermarking for Image Authentication Using the Characteristic of SVD

An Improved Digital Image Watermarking Scheme using Particle Swarm Optimization Technique

Linear weighted watermarking using normalized principal components

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