Affiliation:
1. College of Digital Technology and Engineering, Ningbo University of Finance and Economics, Ningbo 315175, China
2. CKC Software Laboratory, Ningbo University, Ningbo 315211, China
3. School of Electronics and Information Engineering, Ningbo University of Technology, Ningbo 315211, China
Abstract
Video splicing forgery is a common object-based intra-frame forgery operation. It refers to copying some regions, usually moving foreground objects, from one video to another. The splicing video usually contains two different modes of camera sensor pattern noise (SPN). Therefore, the SPN, which is called a camera fingerprint, can be used to detect video splicing operations. The paper proposes a video splicing detection and localization scheme based on SPN, which consists of detecting moving objects, estimating reference SPN, and calculating signed peak-to-correlation energy (SPCE). Firstly, foreground objects of the frame are extracted, and then, reference SPN are trained using frames without foreground objects. Finally, the SPCE is calculated at the block level to distinguish forged objects from normal objects. Experimental results demonstrate that the method can accurately locate the tampered area and has higher detection accuracy. In terms of accuracy and F1-score, our method achieves 0.914 and 0.912, respectively.
Funder
Zhejiang Provincial Natural Science Foundation of China
Natural Science Foundation of Ningbo
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering