Copy-Move Video Forgery Detection Techniques: A Systematic Survey with Comparisons, Challenges and Future Directions

In the real-world scenario, the digital videos are captured to keep in records the life related memories, security purpose, truthful evidence etc. Due to rise in multimedia technology, the digital videos are mostly posted over social websites and applications such as Facebook, Instagram, What's App, YouTube, etc. through the internet in daily routine. The contents of these social digital videos are manipulated by easily available editing tools and software. Therefore, the security of digital videos over social media are the most important requirement of people. This paper presents a systematic survey on Copy-Move forgery and its detection with several passive techniques in the digital videos. At first, Copy-Move forgery is introduced with its various types in this paper. Then, a survey is provided on the existing passive techniques for detecting Copy-Move forgery in digital videos. Here, brief review of techniques is also presented in the tabular forms with their used features, datasets, parameters, type of forgery and their limitations. Furthermore, this survey provides the parameters and datasets in detail which are used for the evaluation of existing techniques. Besides, the detecting tools for Copy-Move video forgery and its future directions are detailed in this survey. This paper also provides various new challenges for automatic detection of Copy-Move video forgery in the realm of deep learning.