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The technology has been hailed as "the most significant development in [[audio forensics]] since [[Watergate scandal|Watergate]]."<ref name="williams_article"/> However, according to a paper by Huijbregtse and Geradts, the ENF technique, although powerful, has significant limitations caused by ambiguity based on fixed frequency offsets during recording, and [[self-similarity]] within the mains frequency database, particularly for recordings shorter than 10 minutes.<ref>Maarten Huijbregtse, Zeno Geradts. {{cite web|url=http://www.forensic.to/ENF%20processed.pdf|title=Using the ENF criterion for determining the time of recording of short digital audio recordings}} Lecture Notes in Computer Science; Vol. 5718, Proceedings of the 3rd International Workshop on Computational Forensics, 2009.</ref>
More recently, researchers demonstrated that indoor lights such as fluorescent lights and incandescent bulbs vary their light intensity in accordance with the voltage supplied, which in turn depends on the voltage supply frequency. As a result, the light intensity can carry the frequency fluctuation information to the visual sensor recordings in a similar way as the electromagnetic waves from the power transmission lines carry the ENF information to audio sensing mechanisms. Based on this result, researchers demonstrated that visual track from still video taken in indoor lighting environments also contain ENF traces that can be extracted by estimating the frequency at which ENF will appear in a video as low sampling frequency of video (25–30 Hz) cause significant aliasing.<ref>Garg Ravi, Varna Avinash L., Wu Min: {{cite
== Use by law enforcement ==
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