Exploiting rolling shutter for ENF signal extraction from video

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Abstract
The electric network frequency (ENF) signal can be embedded in multimedia recordings created in areas of electrical activities. Recent work has used the ENF signal for such applications as time stamp authentication and forgery detection. It is more challenging to extract ENF signals from video recordings than from audio recordings because of the low temporal sampling rate or frame rate of video cameras. The rolling shutter of CMOS image sensor can be exploited as it exposes a frame line by line, and the effective ENF sampling rate by treating each line as a signal sample can be increased. This scheme was shown to work well with static videos. This paper conducts a further study on the exploitation of the rolling shutter for extracting ENF traces from videos. The rolling shutter mechanism is modeled and analyzed using multirate signal processing theory. Challenging cases of videos with motions are examined, and solutions to extracting ENF from them are explored.

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