Detecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approach

Saffet Vatansever, Ahmet Emir Dirik, Nasir Memon

Research output: Contribution to journalArticlepeer-review


Electrical network frequency (ENF) instantaneously fluctuates around its nominal value (50/60 Hz) due to a continuous disparity between generated power and consumed power. Consequently, luminous intensity of a mains-powered light source varies depending on ENF fluctuations in the grid network. Variations in the luminance over time can be captured from video recordings and ENF can be estimated through content analysis of these recordings. In ENF-based video forensics, it is critical to check whether a given video file is appropriate for this type of analysis. That is, if ENF signal is not present in a given video, it would be useless to apply ENF-based forensic analysis. In this letter, an ENF signal presence detection method is introduced for videos. The proposed method is based on multiple ENF signal estimations from steady superpixels, i.e., pixels that are most likely uniform in color, brightness, and texture, and intra-class similarity of the estimated signals. Subsequently, consistency among these estimates is then used to determine the presence or absence of an ENF signal in a given video. The proposed technique can operate on video clips as short as 2 min and is independent of the camera sensor type, i.e., CCD or CMOS.

Original languageEnglish (US)
Article number8012515
Pages (from-to)1463-1467
Number of pages5
JournalIEEE Signal Processing Letters
Issue number10
StatePublished - Oct 2017


  • ENF detection
  • Electrical network frequency (ENF)
  • multimedia forensics
  • superpixel
  • video forensics

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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