Semi-automatic methods in video forgery detection based on multi-view dimension

• Published in: Lecture Notes on Data Engineering and Communications Technologies
• Main Author: Al-Sanjary O.I.; Ghazali N.; Ahmed A.A.; Sulong G.
• Format: Book chapter
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2018
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077528421&doi=10.1007%2f978-3-319-59427-9_41&partnerID=40&md5=c9a1967daa0a539bb87e785e7c2b639a

The availability of powerful editing software sophisticated digital cameras, and region duplication is becoming more and more popular in video manipulation where parts of video frames is pasted to another location to conceal undesirable objects. Most existing techniques to detect such tampering are mainly at the cost of higher computational complexity. Multi-view video contains locating a moving object (or multiple objects) over time and several frames representing different views of the same scene of the true width and height of an object in the front view are placed in the sequences of frames plane. In this paper, a new technique for video forgery detection using semi-automatic methods can be used for the three types of video forgery detection: (1) Copy-Move, (2) Splicing, and (3) Swapping-Frames based on a new dimension of multi-view frames. Thus, this idea is proposing new video views based on slices of video frames in Top-View and Side-View in doctored video. Experiment results show that our proposed schemes for new video views enable easy detection of visual inspection is used for the evaluation. © Springer International Publishing AG 2018.