Double H.264/AVC compression detection using quantized nonzero AC coefficients

Liao, Dandan; Yang, Rui; Li, Hongmei; Li, Jian; Huang, Jijie

doi:10.1117/12.876566

Cited by 29 publications

(18 citation statements)

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“…To expose video compression history, scholars and researchers have put in a lot of effort to study potential characteristics in compressed videos [5,6], such as DCT coefficient distribution [7][8][9], blocking artifacts of MPEG videos [10,11], the first-digit law of DCT coefficients [12,13], Markov-based features [14], prediction unit-based characteristics of HEVC videos [15][16][17], etc. Besides, video trancoding is also one of the common operations in video compression, so the issue of detecting transcoded videos also attracts some attention in the existing literature.…”

Section: Introductionmentioning

confidence: 99%

Exposing Video Compression History by Detecting Transcoded HEVC Videos from AVC Coding

Bian

et al. 2019

Symmetry

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The analysis of video compression history is one of the important issues in video forensics. It can assist forensics analysts in many ways, e.g., to determine whether a video is original or potentially tampered with, or to evaluate the real quality of a re-encoded video, etc. In the existing literature, however, there are very few works targeting videos in HEVC format (the most recent standard), especially for the issue of the detection of transcoded videos. In this paper, we propose a novel method based on the statistics of Prediction Units (PUs) to detect transcoded HEVC videos from AVC format. According to the analysis of the footprints of HEVC videos, the frequencies of PUs (whether in symmetric patterns or not) are distinguishable between original HEVC videos and transcoded ones. The reason is that previous AVC encoding disturbs the PU partition scheme of HEVC. Based on this observation, a 5D and a 25D feature set are extracted from I frames and P frames, respectively, and are combined to form the proposed 30D feature set, which is finally fed to an SVM classifier. To validate the proposed method, extensive experiments are conducted on a dataset consisting of CIF (352 × 288) and HD 720p videos with a diversity of bitrates and different encoding parameters. Experimental results show that the proposed method is very effective at detecting transcoded HEVC videos and outperforms the most recent work.

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Section: Introductionmentioning

confidence: 99%

Exposing Video Compression History by Detecting Transcoded HEVC Videos from AVC Coding

Bian

et al. 2019

Symmetry

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“…High-efficiency video coding (HEVC) is the latest generation of video coding standard prepared by the Joint collaborative Team on Video Coding [3]. Although research works on double compression detection are prosperous on video standards preceding HEVC [4][5][6][7][8][9][10], e.g., MPEG, H.264, the research of double compression detection on HEVC needs more attention. Huang et al [11] utilize cooccurrence matrixes of discrete cosine transform (DCT) coefficients to detect double compressed HEVC videos when the quantization parameters (QP) change in the process of the second compression.…”

Section: Introductionmentioning

confidence: 99%

HEVC double compression detection under different bitrates based on TU partition type

Yang

et al. 2019

J Image Video Proc.

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During the process of authenticating the integrity of digital videos, double compression is an important evidence. High-efficiency video coding (HEVC) is the latest coding standard proposed in 2013 and has shown superior performance over its predecessors. It brings in several novel syntactic units, such as coding tree unit (CTU), prediction unit (PU), and transform unit (TU). Few methods have been reported to detect HEVC double compression by utilizing such new characteristics. In this paper, a novel scheme based on TU is proposed to detect double compression of HEVC videos. The histogram of each TU partition type in the first I/P frame of all GOPs is calculated. The feature set is fed into SVM to classify single and double compressed videos. Experimental results have demonstrated the effectiveness of TU-based feature (accuracy in [0.84, 0.97]) that bears very low dimension (10-D). And it is also shown that TU-based feature set can be combined with other feature sets to boost their performance.

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“…Some methods propose to use noise characteristics [5] to detect possible forgeries. Other works try to detect proofs of the evidence of a double compression [6,7]. Wang and Farid [8] proposed a method to detect duplicated frames used to remove people or objects from a video.…”

Section: State Of the Artmentioning

confidence: 99%

A Tool to Support the Creation of Datasets of Tampered Videos

Ardizzone

Mazzola

2015

Image Analysis and Processing — ICIAP 2015

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Abstract. Digital Video Forensics is getting a growing interest from the Multimedia research community, as the need for methods to validate the authenticity of a video content is increasing with the number of videos freely available to the digital users. Unlike Digital Image Forensics, to our knowledge, there are not standard datasets to test video forgery detection techniques. In this paper we present a new tool to support the users in creating datasets of tampered videos. We furthermore present our own dataset and we discuss some remarks about how to create forgeries difficult to be detected by an observer, to the naked eye.

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Double H.264/AVC compression detection using quantized nonzero AC coefficients

Cited by 29 publications

References 0 publications

Exposing Video Compression History by Detecting Transcoded HEVC Videos from AVC Coding

Exposing Video Compression History by Detecting Transcoded HEVC Videos from AVC Coding

HEVC double compression detection under different bitrates based on TU partition type

A Tool to Support the Creation of Datasets of Tampered Videos

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