A phase-based approach for ENF signal extraction from rolling shutter videos
Hyekyung Han, Youngbae Jeon, Baek-kyung Song, Ji Won Yoon
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Abstract
Electric Network Frequency (ENF) analysis has been an intriguing tool for multimedia forensics as former studies have paved the way for estimating ENF signals from digital audio, video, or even image files. However, for ENF signals to be widely used in extensive applications, supplementary research is needed so that ENF signals can be stably extracted without restrictions. In this letter, we propose a new phase-based approach for extracting ENF signals from CMOS sensor recordings. It uses phase differences between row signals from two consecutive frames, such that problems due to missing sample points during the idle periods are circumvented. The proposed method has substantial advantages in that it is applicable without a predefined read-out time and when the length of given videos is too short. Extensive experiments conducted with numerous devices demonstrate that the proposed method can take precedence over state-of-the-art methods because it robustly produces accurate ENF estimates in terms of alias frequency on the frame-level.