Electric network frequency extraction from videos

• Κύριος συγγραφέας: Μπακταλιά, Ελένη
• Άλλοι συγγραφείς: Baktalia, Eleni
• Γλώσσα: English
• Έκδοση: 2023
• Θέματα: Electric network frequency; Authentication; Video; Συχνότητα ηλεκτρικού δικτύου; Βίντεο; Αυθεντικοποίηση

Electric Network Frequency (ENF) fluctuations are used as an emerging technology for multimedia authentication, timestamping and geolocation in forensics, for video sunchronisation in the film making industry etc. The employed techniques require extracting fluctuations from the recordings in question and comparing them to ground-truth frequencies. The objective of this thesis is the study of different methods and factors affecting the ENF extraction from the visual part of videos. For this purpose, three algorithms were implemented, each one applied to a different video category. The first two, for static global and rolling shutter videos respectively and the last one for non-static global shutter videos. The algorithms for the static cases were presented on white wall videos for simplicity reasons but they were eventually expanded to colorful scenes. Multiple factors can affect the process of ENF extraction so the influence of video compression and type of lightbulb were investigated for both types of shutter. For the non-static videos, a superpixel-based approach was used and different numbers of superpixels were tested in order to determine the least amount needed for the success of the algorithm. The validity of the algorithms was checked by correctly identifying the video’s recording time for all the examined cases. According to the findings of the experiments the results vary depending on the type of shutter. Global shutter videos maintain the same similarity index between the ENF and the ground-truth signal for all kinds of compression when for rolling shutter videos the index is significantly more impacted. Additionally, when it comes to room illumination while incandescent lights produce the finest results for rolling shutter videos, LEDs perform best for global shutter videos. The superpixel technique works for both static and non-static videos, and the more movement is incorporated into the video, the more superpixels are required for the correct timestamping.