Detecting double H.264 compression based on analyzing prediction residual distribution

S. Chen, T. F. Sun, X. H. Jiang, P. S. He, S. L. Wang, Y. Q. Shi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Detecting double video compression has become an important issue in video forensics. A novel double H.264 compression detection scheme based on Prediction Residual Distribution (PRED) analysis is proposed in the paper. The proposed scheme can be applied to detect double H.264 compression with non-aligned GOP structures. For each frame of a given video, the prediction residual is first calculated and the average value of the prediction residual in each non-overlapping 4 4 block is recorded to reduce the influence of the noise. Then the PRED feature is represented by the distribution of the average prediction residual in each frames. After that, the Jensen-Shannon Divergence (JSD) is introduced to measure the difference between the PRED features of adjacent two frames. Finally, a Periodic Analysis (PA) method is applied to the final feature sequence to detect double H.264 compression and to estimate the first GOP size. Fourteen public YUV sequences are adopted for evaluation. Experiments have demonstrated that the proposed scheme can achieve better performance than the state-of-the-art method investigated.

Original languageEnglish (US)
Title of host publicationDigital Forensics and Watermarking - 15th International Workshop, IWDW 2016, Revised Selected Papers
EditorsHyoung Joong Kim, Feng Liu, Fernando Perez-Gonzalez, Yun Qing Shi
PublisherSpringer Verlag
Pages61-74
Number of pages14
ISBN (Print)9783319534640
DOIs
StatePublished - 2017
Event15th International Workshop on Digital-Forensics and Watermarking, IWDW 2016 - Beijing, China
Duration: Sep 17 2016Sep 19 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10082 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Workshop on Digital-Forensics and Watermarking, IWDW 2016
CountryChina
City Beijing
Period9/17/169/19/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • Double compression detection
  • First GOP estimation
  • Non-aligned GOP structure
  • Prediction residual distribution

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