A Contrario Detection of H.264 Video Double Compression

  • Yanhao Li
  • , Marina Gardella
  • , Quentin Bammey
  • , Tina Nikoukhah
  • , Jean Michel Morel
  • , Miguel Colom
  • , Rafael Grompone Von Gioi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Video manipulation detection plays a vital role in modern multimedia forensics. In particular, double compression detection provides significant clues leading to the video edition history and hinting at potential malevolent manipulation. While such an analysis is well-understood on images, the research on this subject remains lacking in videos and existing methods are not yet able to reliably detect double-compressed videos. This work presents a novel method for identifying double compression in H.264 codec videos. Our technique exploits the periodicity of frame residuals caused by fixed Group of Pictures in the initial compression, and employs an a contrario framework to minimize and control false detections. The proposed method can reliably detect double compression in videos. It does not require threshold tuning, thus enabling automatic detection. The code is available at https://github.com/li-yanhao/gop-detection.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Image Processing, ICIP 2023 - Proceedings
PublisherIEEE Computer Society
Pages1765-1769
Number of pages5
ISBN (Electronic)9781728198354
DOIs
Publication statusPublished - 1 Jan 2023
Externally publishedYes
Event30th IEEE International Conference on Image Processing, ICIP 2023 - Kuala Lumpur, Malaysia
Duration: 8 Oct 202311 Oct 2023

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference30th IEEE International Conference on Image Processing, ICIP 2023
Country/TerritoryMalaysia
CityKuala Lumpur
Period8/10/2311/10/23

Keywords

  • Video double compression
  • a contrario
  • deepfake detection
  • group of pictures
  • video forensics

Fingerprint

Dive into the research topics of 'A Contrario Detection of H.264 Video Double Compression'. Together they form a unique fingerprint.

Cite this