Digital Video Manipulation Detection Technique Based on Compression Algorithms

2021 ◽  
pp. 1-10
Author(s):  
Edgar Gonzalez Fernandez ◽  
Ana Lucila Sandoval Orozco ◽  
Luis Javier Garcia Villalba
Keyword(s):  
Digital Video ◽  
Detection Technique ◽  
Compression Algorithms ◽  
Video Manipulation ◽  
Manipulation Detection

Passive Video Tampering Detection Using Noise Features

2016 ◽  
pp. 279-303
Author(s):  
Ramesh Chand Pandey ◽  
Sanjay Kumar Singh ◽  
K. K. Shukla
Keyword(s):  
Digital Signature ◽  
Digital Video ◽  
Low Cost ◽  
Digital Watermark ◽  
Detection Technique ◽  
Video Editing ◽  
Tampering Detection ◽  
Detection Techniques ◽  
Processing Pipeline ◽  
Active Video

With increasing availability of low-cost video editing softwares and tools, the authenticity of digital video can no longer be trusted. Active video tampering detection technique utilize digital signature or digital watermark for the video tampering detection, but when the videos do not include such signature then it is very challenging to detect tampering in such video. To detect tampering in such video, passive video tampering detection techniques are required. In this chapter we have explained passive video tampering detection by using noise features. When video is captured with camera it passes through a Camera processing pipeline and this introduces noise in the video. Noise changes abruptly from authentic to forged frame blocks and provides a clue for video tampering detection. For extracting the noise we have considered different techniques like denoising algorithms, wavelet based denoising filter, and neighbor prediction.

BLUE SCREEN VIDEO FORGERY DETECTION AND LOCALIZATION USING AN ENHANCED 3-STAGE FOREGROUND ALGORITHM

2021 ◽  
Vol 5 (2) ◽  
pp. 133-144
Author(s):  
Kasim Shafii ◽  
Mustapha Aminu Bagiwa ◽  
A. A. Obiniyi ◽  
N. Sulaiman ◽  
A. M. Usman ◽  
...  
Keyword(s):  
Detection Rate ◽  
Digital Video ◽  
Gaussian Mixture ◽  
Detection Technique ◽  
Video Editing ◽  
Digital Videos ◽  
Positive Detection Rate ◽  
Video Forgery Detection ◽  
Video Forgery ◽  
Detection And Localization

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

Clinical Application and Results of the Assessment of Coronary Blood Flow by the Regional Precordial Xenon Residue Detection Technique

1978 ◽  
Vol 17 (04) ◽  
pp. 161-171
Author(s):  
H.-J. Engel ◽  
H. Hundeshagen ◽  
P. R. Lichtlen
Keyword(s):  
Wall Motion ◽  
High Flow ◽  
Detection Technique ◽  
Fatty Tissue ◽  
Technical Aspects ◽  
Residue Detection ◽  
High Affinity ◽  
Artery Disease ◽  
The Right ◽  
Drug Interventions

Methodological and technical aspects as well as application and results of the precordial Xenon-residue-detection technique are critically reviewed. The results concern mainly normal flow in various regions of the heart esp. in the free wall of the right and left ventricle, poststenotic flow in patients with coronary artery disease in relation to the degree of proximal nar-rowings as well as wall motion of the corresponding LV segment, bypassgraft flow and flow after drug interventions esp. nitrates, betablockers, the calcium-antagonist Nifedipine and the coronary dilator Dipyridamole. In spite of its serious limitations (high affinity of Xenon for fatty tissue, geometrical problems in the assessment of flow and its relation to anatomy, gas exchange in situations of high flow etc.), the technique is found to be a usefull investigatory tool. Due to its technical display and the related high costs routine application is, however, prohibitive.

Template Detection Technique From Assorted Web Pages

2012 ◽  
Vol 2 (9) ◽  
pp. 148-150 ◽  
Author(s):  
Marriboyina Rajendra ◽  
◽  
S. Suresh Babu
Keyword(s):  
Detection Technique ◽  
Web Pages
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