Exposing digital video forgery by ghost shadow artifact

Author(s):  
Jing Zhang ◽  
Yuting Su ◽  
Mingyu Zhang
Keyword(s):  
Author(s):  
Ruksana Habeeb ◽  
L. C. Manikandan

Technological advancements of various video and image editing tools has reached such a level that the tampering of digital video or image can be performed easily without degrading their quality or leaving any visual evidence. This review paper presents an overview of various types of video forgery and the different types of techniques that are employed for its detection. Passive and active forgery detection techniques are commonly used methods for detecting the tampering in a digital video. Passive and active tampering detection techniques are utilized for detecting the integrity as well as the authenticity of a given video. The aim of this review is to provide some productive information about video tampering attacks for upcoming researchers.


-We are living in the era of multimedia technology. Digital video occupies an imperative role in our daily life. With the use of omnipresent multimedia technology, we can create process, transmit and store digital information in many forms such as an image, audio and video. Digital video is convenient tool in forensic investigation, medical treatment, education, entertainment and other disparate fields. Videos are recorded by the people with their smart phones, camcorders, digital cameras and CCTV cameras. We have seen the rapid growth and development in the use of surveillance cameras. Videos recorded using these electronic and smart gadgets mostly contain crucial proof of most of the events. Inasmuch, the most affected to inter frame forgery which can be freely done by replication, insertion, removal and deletion of frames. However, the advancement and usage of inexpensive and effortless video editor software there has been tremendous growth in the consequences and risks of usage such editing techniques. Therefore, forgery is a technique of getting altered, fake and duplicate videos by joining, altering new video. Hence, the genuineness of such digital videos questionable and requires to be verified. In this paper review various video forgery detection methods those are applied to detect whether the video is original or duplicate, real or fake and digital video authentication techniques.


2021 ◽  
Vol 5 (2) ◽  
pp. 133-144
Author(s):  
Kasim Shafii ◽  
Mustapha Aminu Bagiwa ◽  
A. A. Obiniyi ◽  
N. Sulaiman ◽  
A. M. Usman ◽  
...  

The availability of easy to use video editing software has made it easy for cyber criminals to combine different videos from different sources using blue screen composition technology. This, makes the authenticity of such digital videos questionable and needs to be verified especially in the court of law. Blue Screen Composition is one of the ways to carry out video forgery using simple to use and affordable video editing software. Detecting this type of video forgery aims at revealing and observing the facts about a video so as to conclude whether the contents of the video have undergone any unethical manipulation. In this work, we propose an enhanced 3-stage foreground algorithm to detect Blue Screen manipulation in digital video. The proposed enhanced detection technique contains three (3) phases, extraction, detection and tracking. In the extraction phase, a Gaussian Mixture Model (GMM) is used to extract foreground element from a target video. Entropy function as a descriptive feature of image is extracted and calculated from the target video in the detection phase. The tracking phase seeks to use Minimum Output Sum of Squared Error (MOSSE) object tracking algorithm to fast track forged blocks of small sizes in a digital video. The result of the experiments demonstrates that the proposed detection technique can adequately detect Blue Screen video forgery when the forged region is small with a true positive detection rate of 98.02% and a false positive detection rate of 1.99%. The result of this our research can be used to


1989 ◽  
Vol 43 (12) ◽  
pp. 1404-1406
Author(s):  
Taizo Kinoshita ◽  
Tomoko Nakahashi ◽  
Yoshizumi Eto

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