Perceptual video hashing robust against geometric distortions

2012 ◽  
Vol 55 (7) ◽  
pp. 1520-1527 ◽  
Author(s):  
ShiJun Xiang ◽  
JianQuan Yang ◽  
JiWu Huang
Keyword(s):  
Geometric Distortions ◽  
Video Hashing ◽  
Perceptual Video Hashing

scholarly journals Perceptual hashing method for video content authentication with maximized robustness

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Qiang Ma ◽  
Ling Xing
Keyword(s):  
Optimization Problem ◽  
Optimization Method ◽  
Perceptual Content ◽  
Video Content ◽  
Content Authentication ◽  
Constrained Optimization Problem ◽  
Video Hashing ◽  
Perceptual Hashing ◽  
Video Content Authentication ◽  
Perceptual Video Hashing

AbstractPerceptual video hashing represents video perceptual content by compact hash. The binary hash is sensitive to content distortion manipulations, but robust to perceptual content preserving operations. Currently, boundary between sensitivity and robustness is often ambiguous and it is decided by an empirically defined threshold. This may result in large false positive rates when received video is to be judged similar or dissimilar in some circumstances, e.g., video content authentication. In this paper, we propose a novel perceptual hashing method for video content authentication based on maximized robustness. The developed idea of maximized robustness means that robustness is maximized on condition that security requirement of hash is first met. We formulate the video hashing as a constrained optimization problem, in which coefficients of features offset and robustness are to be learned. Then we adopt a stochastic optimization method to solve the optimization. Experimental results show that the proposed hashing is quite suitable for video content authentication in terms of security and robustness.

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