JPEG Error Analysis and Its Applications to Digital Image Forensics

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

doi:10.1109/tifs.2010.2051426

Cited by 253 publications

(142 citation statements)

References 26 publications

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“…It should be noted that when the size of the image patch is small, e.g., 64 × 64, the total number of DCT coefficients is small (64 coefficients in total), and it is difficult to estimate the actual distribution of the patch accurately and robustly using such limited data. In order to solve the above problem of inadequate data, the 1-D feature similar to that in [23] is adopted to differentiate between SDJPEG and SSJPEG image patches as follows: Since the SSJPEG patch has never been compressed with the block structure starting from the top-left corner of the image patch, the DCT coefficients of SSJPEG can be assumed distributed approximately as the original uncompressed image patch [8,14]. Moreover, h SS m;n f ð Þ is equivalent to the distribution of the quantization error of the (m,n)th DCT component with the quantization step q m,n .…”

Section: Detection Of Image Patch With Sdjpeg Compressionmentioning

confidence: 99%

Detection of shifted double JPEG compression by an adaptive DCT coefficient model

Wang

Liew

et al. 2014

EURASIP J. Adv. Signal Process.

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In many JPEG image splicing forgeries, the tampered image patch has been JPEG-compressed twice with different block alignments. Such phenomenon in JPEG image forgeries is called the shifted double JPEG (SDJPEG) compression effect. Detection of SDJPEG-compressed patches could help in detecting and locating the tampered region. However, the current SDJPEG detection methods do not provide satisfactory results especially when the tampered region is small. In this paper, we propose a new SDJPEG detection method based on an adaptive discrete cosine transform (DCT) coefficient model. DCT coefficient distributions for SDJPEG and non-SDJPEG patches have been analyzed and a discriminative feature has been proposed to perform the two-class classification. An adaptive approach is employed to select the most discriminative DCT modes for SDJPEG detection. The experimental results show that the proposed approach can achieve much better results compared with some existing approaches in SDJPEG patch detection especially when the patch size is small.

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Section: Detection Of Image Patch With Sdjpeg Compressionmentioning

confidence: 99%

Detection of shifted double JPEG compression by an adaptive DCT coefficient model

Wang

Liew

et al. 2014

EURASIP J. Adv. Signal Process.

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“…The overall detection performance of any JPEG-compatibility detector will necessarily strongly depend on the accuracy of the estimator of θ as well as the prior distribution of θ in the testing set. Despite some encouraging work, such as [11], we consider the problem of estimating θ as an open and quite difficult problem for the following reasons. Most JPEG images today originate in digital cameras, which, unfortunately, almost exclusively use quantization tables customized for the image content, the imaging sensor, the manufacturer's color space, and the image size [17].…”

Section: Robustness To Jpeg Compressor Parametersmentioning

confidence: 99%

“…Thus, the search space may be quite large even when one considers estimating only the quantization tables themselves. Methods that estimate the individual quantization steps, such as [6,11,10], may fail for high compression ratios as there may be little or no data in the JPEG file to estimate the quantization steps for sparsely populated medium-high frequency DCT modes.…”

Section: Robustness To Jpeg Compressor Parametersmentioning

confidence: 99%

JPEG-Compatibility Steganalysis Using Block-Histogram of Recompression Artifacts

Kodovský

Fridrich

2013

Information Hiding

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Abstract. JPEG-compatibility steganalysis detects the presence of embedding changes using the fact that the stego image was previously JPEG compressed. Following the previous art, we work with the difference between the stego image and an estimate of the cover image obtained by recompression with a JPEG quantization table estimated from the stego image. To better distinguish recompression artifacts from embedding changes, the difference image is represented using a feature vector in the form of a histogram of the number of mismatched pixels in 8 × 8 blocks. Three types of classifiers are built to assess the detection accuracy and compare the performance to prior art: a clairvoyant detector trained for a fixed embedding change rate, a constant false-alarm rate detector for an unknown change rate, and a quantitative detector. The proposed approach offers significantly more accurate detection across a wide range of quality factors and embedding operations, especially for very small change rates. The technique requires an accurate estimate of the JPEG compression parameters.

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“…The DCT coefficient histograms of the re-compressed images are compared to that of the original image; the primary quantization table is selected as the one having minimum distance from the original DCT coefficient histogram. Following this seminal work, Luo and others [66] propose another similarity criteria based on the analysis of JPEG rounding errors. The method is shown to be more accurate than that in [63].…”

Section: Tampering Detection Independent On the Type Of Forgerymentioning

confidence: 99%

Digital image forensics: a booklet for beginners

Redi

Taktak

Dugelay

2010

Multimed Tools Appl

305

115

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Digital visual media represent nowadays one of the principal means for communication. Lately, the reliability of digital visual information has been questioned, due to the ease in counterfeiting both its origin and content. Digital image forensics is a brand new research field which aims at validating the authenticity of images by recovering information about their history. Two main problems are addressed: the identification of the imaging device that captured the image, and the detection of traces of forgeries. Nowadays, thanks to the promising results attained by early studies and to the always growing number of applications, digital image forensics represents an appealing investigation domain for many researchers. This survey is designed for scholars and IT professionals approaching this field, reviewing existing tools and providing a view on the past, the present and the future of digital image forensics.

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JPEG Error Analysis and Its Applications to Digital Image Forensics

Cited by 253 publications

References 26 publications

Detection of shifted double JPEG compression by an adaptive DCT coefficient model

Detection of shifted double JPEG compression by an adaptive DCT coefficient model

JPEG-Compatibility Steganalysis Using Block-Histogram of Recompression Artifacts

Digital image forensics: a booklet for beginners

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