A Video Splicing Forgery Detection and Localization Algorithm Based on Sensor Pattern Noise

Video splicing forgery is a common object-based intra-frame operation. It refers to copying some regions, usually moving foreground objects, from one video another. The contains two different modes of camera sensor pattern noise (SPN). Therefore, the SPN, which called fingerprint, can be used detect operations. paper proposes detection and localization scheme based on consists detecting estimating reference calculating signed peak-to-correlation energy (SPCE). Firstly, objects frame are extracted, then, SPN trained using frames without objects. Finally, SPCE calculated at block level distinguish forged normal Experimental results demonstrate that method accurately locate tampered area has higher accuracy. In terms accuracy F1-score, our achieves 0.914 0.912, respectively.