Quantization Table Estimation in JPEG Images

Hamdy, Salma; El-Messiry, Haytham; Roushdy, Mohamed; Kahlifa, Essam

doi:10.14569/ijacsa.2010.010603

Cited by 9 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hausdorff distance [13] was widely used in shape matching measurement and we used a revised version [5] to reflect the "average" other than only the maximum distance of two area. The distance between boundaries of detected area …”

Section: A Evaluation Criteriamentioning

confidence: 99%

“…By estimating the pattern or level of noise in different regions the forgery can be exposed via noise discrepancies. Prior work has been made by Guo et al [5] but they only provided simulation results rather than actual fake image forensics and did not demonstrate the valid authentication results. While we will discuss and show it in details in the paper.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Splicing Forgery Exposure in Digital Image by Detecting Noise Discrepancies

Liu¹,

Pun²

2015

IJCCE

View full text Add to dashboard Cite

Abstract-We propose a novel technique in this paper to expose splicing forgery in digital images. The forged area spliced from other picture contains some features which may be inconsistent with the rest part of image. Noise pattern and level is a possible factor to reveal such inconsistency. To detect such noise discrepancies, the test picture is initially segmented into small pieces by SLIC superpixels algorithm. The noise pattern and level of each segment is then estimated by using various filters. The noise features constructed in this step are utilized in energy-based graph cut to expose forged area in the final step. Experimental results show that our method provides good illustration of regions with noise inconsistency in various scenarios.

show abstract

Section: A Evaluation Criteriamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Splicing Forgery Exposure in Digital Image by Detecting Noise Discrepancies

Liu¹,

Pun²

2015

IJCCE

View full text Add to dashboard Cite

show abstract

“…Estimating the quantization matrix used in JPEG compression, regions that possess inconsistent DCT coefficients are regarded as splicing area since an intact JPEG format picture should be coded by only one quantization table. Hamdy et al developed this idea in [ 6 ]. However, this approach fails to deal with double compression.…”

Section: Introductionmentioning

confidence: 99%

Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies

Liu¹,

Pun²,

Yuan³

2014

The Scientific World Journal

View full text Add to dashboard Cite

Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image.

show abstract