Inter-frame passive-blind forgery detection for video shot based on similarity analysis

2018 ◽  
Vol 77 (19) ◽  
pp. 25389-25408 ◽  
Author(s):  
Dong-Ning Zhao ◽  
Ren-Kui Wang ◽  
Zhe-Ming Lu
Author(s):  
K. N. Sowmya ◽  
H. T. Basavaraju ◽  
B. H. Lohitashva ◽  
H. R. Chennamma ◽  
V. N. Manjunath Aradhya

2018 ◽  
Vol 7 (4.6) ◽  
pp. 373
Author(s):  
Anto Crescentia.A ◽  
Sujatha. G

Video tampering and integrity detection can be defined as methods of alteration of the contents of the video which will enable it to hide objects, an occasion or adjust the importance passed on by the collection of images in the video. Modification of video contents is growing rapidly due to the expansion of the video procurement gadgets and great video altering programming devices. Subsequently verification of video files is transforming into something very vital. Video integrity verification aims to search out the hints of altering and subsequently asses the realness and uprightness of the video. These strategies might be ordered into active and passive techniques. Therefore our area of concern in this paper is to present our views on different passive video tampering detection strategies and integrity check. Passive video tampering identification strategies are grouped into consequent three classifications depending on the type of counterfeiting as: Detection of double or multiple compressed videos, Region altering recognition and Video inter-frame forgery detection. So as to detect the tampering of the video, it is split into frames and hash is generated for a group of frames referred to as Group of Pictures. This hash value is verified by the receiver to detect tampering.    


2017 ◽  
Vol 76 (24) ◽  
pp. 25767-25786 ◽  
Author(s):  
Staffy Kingra ◽  
Naveen Aggarwal ◽  
Raahat Devender Singh

2019 ◽  
Vol 13 (3) ◽  
pp. 522-528 ◽  
Author(s):  
Sondos M. Fadl ◽  
Qi Han ◽  
Qiong Li

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