PRNU Estimation based on Weighted Averaging for Source Smartphone Video Identification

Ashref Lawgaly, Fouad Khelifi, Ahmed Bouridane, Somaya Al-Maaddeed, Younes Akbari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Photo response non-uniformity (PRNU) noise is a sensor pattern noise characterizing imperfections in the imaging device. The PRNU is a unique noise for each sensor device, and it has been generally utilized in the literature for source camera identification and image authentication. In video forensics, the traditional approach estimates the PRNU by averaging a set of residual signals obtained from multiple video frames. However, due to lossy compression and other non-unique content-dependent noise components that interfere with the video data, constant averaging does not take into account the intensity of these undesirable noise components which are content-dependent. Different from the traditional approach, we propose a video PRNU estimation method based on weighted averaging. The noise residual is first extracted for each single video. Then, the estimated noise residuals are fed into a weighted averaging method to optimize PRNU estimation. Experimental results on two video datasets captured by various smartphone devices have shown a significant gain obtained with the proposed approach over the conventional state-of-the-art one.
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Control, Decisions and Information Technologies
Subtitle of host publication(CODIT 2022)
PublisherIEEE
Number of pages6
Publication statusAccepted/In press - 11 Mar 2022
Event8th International Conference on Control, Decision and Information Technologies: CoDIT'22 - Istanbul, Turkey
Duration: 17 May 202220 May 2022
https://codit2022.com/

Conference

Conference8th International Conference on Control, Decision and Information Technologies
Country/TerritoryTurkey
CityIstanbul
Period17/05/2220/05/22
Internet address

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