ENF Signal Extraction for Rolling-shutter Videos Using Periodic Zero-padding

Choi, Jisoo; Wong, Chau-Wai

doi:10.1109/icassp.2019.8682894

Cited by 17 publications

(14 citation statements)

References 12 publications

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“…Fig. 4(a) shows three simulated pixel intensity signals I (t) driven by the different voltage models in (23). We used the same supply voltage measurement in Section III-A to generate the three simulated voltage signals.…”

Section: Appendix B Attribution Of Artifacts Of Time-varying Behaviormentioning

confidence: 99%

Invisible Geolocation Signature Extraction From a Single Image

Choi¹,

Wong²,

Hajj-Ahmad³

et al. 2023

Preprint

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Section: Appendix B Attribution Of Artifacts Of Time-varying Behaviormentioning

confidence: 99%

Invisible Geolocation Signature Extraction From a Single Image

Choi¹,

Wong²,

Hajj-Ahmad³

et al. 2023

Preprint

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“…This work shall show that the rolling shutter's sequential readout time mechanism allows the resulting image to capture samples of an incident light signal at slightly different time instants and thus obtain a short segment of ENF traces. Studies on ENF from audio [11], [15] and videos [16], [19], [22], [23] show that one frequency estimate of audio and video recordings requires a signal of 5-10 and 12-20 seconds long, respectively. In contrast, the available signal length allowed by a single rolling-shutter image is only about 0.02-0.03 seconds, corresponding to about 2-3.6 cycles that are not long enough to observe ENF fluctuations.…”

Section: B Rolling Shutter and Read-out Timementioning

confidence: 99%

“…The result of (23) shows that the light intensity L i has a linear relationship in u that can be related to the row index i of the image. When the light reflecting off the object's surface travels through the camera lens, in the case of DSLR cameras, it is turned upside-down and then flipped over again by a pentaprism.…”

Section: Appendix a Light Intensity As A Function Of Row Indexmentioning

confidence: 99%

Invisible Geolocation Signature Extraction From a Single Image

Choi

Wong

Hajj-Ahmad

et al. 2022

IEEE Trans.Inform.Forensic Secur.

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Geotagging images of interest are increasingly important to law enforcement, national security, and journalism. Today, many images 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 environmental signature from the power grid, the electric network frequency (ENF) signal, which can be inherently captured in a sensing stream at the time of recording and carries useful time-location information. Compared to the recent art of extracting ENF traces from audio and video recordings, it is very challenging to extract an ENF trace from a single image. We address this challenge by first mathematically examining the impact of the ENF embedding steps such as electricity to light conversion, scene geometry dilution of radiation, and image sensing. We then incorporate the verified parametric models of the physical embedding process into our proposed entropy minimization method. The optimized results of the entropy minimization are used for creating a two-level ENF presence-classification test for region-of-capturing localization. It identifies whether a single image has an ENF trace; if yes, whether it is at 50 or 60 Hz. We quantitatively study the relationship between the ENF strength and its detectability from a single image. This paper is the first comprehensive work to bring out a unique forensic capability of environmental traces that shed light on an image's capturing location.

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“…While working on extending our preliminary results on periodic zeroing-out presented at ICASSP 2019 [2], we became aware of a parallel effort by Vatanseve et al [27], which also used multirate signal processing to analyze ENF in videos acquired by rolling shutters. In light of the similar submission time of [2] and [27], we believe that the two lines of research were conducted in parallel. Both papers were inspired from our earlier results published at ICASSP 2014 [1].…”

Section: B Comparison With Parallel Workmentioning

confidence: 99%

“…In addition to the multirate analysis for the direct concatenation method and the periodic zeroing-out method proposed in our preliminary work [1], [2], we summarize the contributions of this paper as follows:…”

Section: Introductionmentioning

confidence: 99%