Geo-tagging images of interest is increasingly important to law enforcement, national security, and journalism. Many images today do not carry location tags that are trustworthy and resilient to tampering; and the landmark-based visual clues may not be readily present in every image, especially in those taken indoors. In this paper, we exploit an invisible signature from the power grid, the Electric Network Frequency (ENF) signal, which can be inherently recorded in a sensing stream at the time of capturing and carries useful location information. It is, however, very challenging to extract an ENF signal from a single image, as compared to the recent art in extracting ENF traces from audio and video. This paper presents novel investigations toward this challenge, by synergistically exploring the rolling shutter effect of CMOS imaging sensors and entropy differences of composite signals. We study quantitatively the relationship between the ENF strength and its detectability from a single image, and bring out a unique forensics capability of invisible traces that shine a light on an image's capturing location.

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