An effective SVD-based image tampering detection and self-recovery using active watermarking

Dadkhah, Sajjad; Manaf, Azizah Abdul; Hori, Yoshiaki; Hassanien, Aboul Ella; Sadeghi, Somayeh

doi:10.1016/j.image.2014.09.001

Cited by 96 publications

(42 citation statements)

References 16 publications

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“…(1) For the blocks whose 2 LSBs are embedded by 8 bits watermark information, the expectation value of MSE is 1.5 2 , then the PSNR's expectation can be computed by: PSNR = 10 log 10 ( 255 2 1.5 2 ) = 44.61 (dB), (12) (2) For the blocks whose 3 LSBs are embedded by 12 bits watermark information, the expectation value of MSE is 3.5 2 , then the PSNR's expectation is calculated by: PSNR = 10 log 10 ( 255 2 3.5 2 ) = 37.25 (dB), (13) In practical application, if the PSNR value of a processed image is larger than 35 dB, people cannot tell the difference between the original image and its processed version. Table 2 gives the analysis of watermark imperceptibility for the test images shown in Figure 5.…”

Section: Imperceptibility Analysismentioning

confidence: 99%

“…In addition, the recovered image could be further used for the subsequent image processing. In fragile watermarking scheme with recovery ability, the recovery information for an image block is usually a content representation of the block, like average pixel value [12,13], vector quantization (VQ) index [14], the discrete cosine transform (DCT) coefficients [15,16], etc.…”

Section: Introductionmentioning

confidence: 99%

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A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

2018

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Currently, the watermark capacity of most self-recovery fragile image watermarking schemes is fixed. That means for smooth regions and texture regions, the length of watermark information is always the same. However, it is impractical since more recovery information is needed for the recovery of texture regions. In this paper, a self-recovery fragile image watermarking with variable watermark capacity is proposed. Based on the characteristic of singular value decomposition (SVD), a new block classification method is introduced. The image blocks are classified into smooth blocks and texture blocks. For smooth blocks, the average pixel values are adopted as the recovery information to recover the tampered blocks, while for texture blocks, the quantized and coded DCT coefficients are adopted as the recovery information. After encrypted by binary pseudo-random sequence, the recovery watermark of each block is embedded into its mapping block. In the detection side, the three-level detection mechanism is applied to detect and locate the tampered regions. The experimental results prove that the proposed method achieves good tamper detection results, and the recovered image has better image quality than other self-recovery fragile watermarking methods.

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Section: Imperceptibility Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

2018

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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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“…As digital media is becoming an ever-more integral part of daily life, digital image, audio, and video are increasingly being presented in courts of law as evidence of criminal activity or wrongdoing [1]. However, the authenticity of a given digital image has become more difficult to validate, as a consequence of the drastic changes in the production, editing and dissemination of digital image.…”

Section: Introductionmentioning

confidence: 99%

Keypoint Based Authentication And Localization Of Copy-Move Forgery In Digital Image

Sadeghi

Jalab

Wong

et al. 2017

MJCS

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With the development of powerful image processing tools and the increasing trend of using images as the main carrier of information, digital image forgery has become an increasingly serious issue. In copy-move forgery, one part of an image is copied and placed elsewhere in the same image. This paper puts forward an effective method based on SIFT for detecting copy-move forgery in digital image. The proposed method can accurately authenticate digital image and locate areas which have been tampered with. The algorithm starts by using scale-invariant features transform (SIFT) to extract local image features, which are known as keypoints, and then searches for similar keypoints based on their Euclidean distances. Finally, the matched keypoints, which represent the copied and pasted areas, are associated with one and another to indicate which parts of the image have been tampered with. Experiments are performed to validate the effectiveness of this method on different attacks, and to quantify its robustness against post-processing. Results show that the method is robust against several geometric processings, including JPEG compression, rotation, noise, and scaling. As a representative result, when considering the standard test dataset MICC-F220, the proposed method achieves true and false positive rates of 100% and 3.12%, respectively.

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An effective SVD-based image tampering detection and self-recovery using active watermarking

Cited by 96 publications

References 16 publications

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

Fragile Watermarking for Image Authentication Using the Characteristic of SVD

Keypoint Based Authentication And Localization Of Copy-Move Forgery In Digital Image

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