Employing SVD and Wavelets for Digital Image Forensics and Tampering Detection

Bhosale, S. P.; Thube, Ganesh; Jangam, Pooja; Borse, Rushikesh

doi:10.1109/mncapps.2012.35

Cited by 4 publications

(2 citation statements)

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“…In 2012 [8], discrete wavelet transform coefficients were used to get featured vectors. Unlike other existing algorithms, this algorithm works even when the doctored image is truncated.…”

Section: Introductionmentioning

confidence: 99%

Digital image copy-move forgery detection based on discrete fractional wavelet transform

2018

Turk J Elec Eng & Comp Sci

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Abstract:With the advancement of sophisticated cameras and image editing software tools, digital image tampering techniques are frequently used without leaving visual cues behind. Digital image copy-move forgery is a kind of image manipulation that involves copying and pasting of a certain section (or sections) within the same digital image. Generally, this is done with false intentions of hiding important information or providing false information in an image. In view of this, the focus of the present paper is to propose a discrete fractional wavelet transform-based scheme for identification of duplicated regions in the image. The test image is split into overlapping image blocks with fixed dimensions. Then, on each image block, discrete fractional wavelet transform is employed for the extraction of their features. All the feature vectors are systematized in lexicographical manner followed by the block matching and block filtering steps to obtain the replicated blocks, if any. The proposed method can detect single and multiple duplicated regions successfully. The results are compared to existing techniques based on precision and recall parameters. Simulation results show that the proposed forgery detection scheme can detect tampering areas even in the presence of distortions due to Gaussian blurring and JPEG compression.

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“…In 2012 [8], discrete wavelet transform coefficients were used to get featured vectors. Unlike other existing algorithms, this algorithm works even when the doctored image is truncated.…”

Section: Introductionmentioning

confidence: 99%

Digital image copy-move forgery detection based on discrete fractional wavelet transform

2018

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

show abstract

“…Also, the algorithm attaches only binary watermark images and it became computationally inefficient, since it used vector quantization algorithm for the optimization of adaptive quantization parameters, while indexing the blocks. Many other algorithms (Bhosale et al, 2012;Chen et al, 2012;Coatrieux et al, 2012;Ishikawa et al, 2012;Kandpal et al, 2012;Vargas et al, 2013;Varghese et al, 2014;Walia et al, 2013;Wang et al, 2011;Wang et al, 2012;Wu et al, 2005;Yang et al, 2010;Zareian et al, 2013) also developed in the literature by meeting some requirements of watermarking, but these algorithms also failed in simultaneously meeting other vital requirements of watermarking (Mason et al, 2000) including perceptibility, robustness, orthogonality, protection against attacks etc.…”

Section: Introductionmentioning

confidence: 99%