The Effect of Inverse Square Law of Light on ENF in Videos Exposed by Rolling Shutter


Vatansever S., DİRİK A. E., Memon N.

IEEE Transactions on Information Forensics and Security, vol.18, pp.248-260, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 18
  • Publication Date: 2023
  • Doi Number: 10.1109/tifs.2022.3220029
  • Journal Name: IEEE Transactions on Information Forensics and Security
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.248-260
  • Keywords: camera forensics, electric network frequency, ENF, frame rate harmonics, idle period, multimedia forensics, rolling shutter, time-of-recording, time-stamp verification, video forensics
  • Bursa Uludag University Affiliated: Yes

Abstract

IEEEDue to a constant imbalance between demand and supply of power, ENF (Electric Network Frequency) fluctuates around a nominal value of 50 or 60 Hz. These variations in ENF cause the luminance intensity of a mains-powered light source, having no AC/DC converter inside, also to fluctuate. As a result, a video of a scene illuminated by a mains-powered light source can be used to estimate these fluctuations. As a consequence, the ENF signal within the time period when the video was captured can be estimated. This work explores the effects of frame rate harmonics that emerge when a rolling shutter based approach is used for ENF estimation from videos captured using CMOS cameras. These harmonics are a problem, especially for videos whose frame rate is a divisor of the nominal ENF because the frame rate harmonics and the ENF harmonics overlap. It is discovered that a key reason for the presence of the harmonics is the inverse square law of light that results in some repeating patterns of luminance variation across frames. This paper presents an analysis of the effect of the inverse square law of light on ENF estimation. A technique for refined ENF-related luminance signal estimation is proposed that attenuates these frame rate harmonics. This enables more accurate ENF estimates. The work also proposes an approach to estimate ENF-related luminance waveform cycles within each video frame, and a method to compute the confidence score for the estimated cycles. It provides insight into the reliability of the extracted ENF signal from a video, in the sense of its usefulness for ENF forensics, and consequently for ENF detection, which is an important precursor to ENF-based video forensics.