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Passive Video Tampering Detection Using Noise Features
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Author(s): Ramesh Chand Pandey (Indian Institute of Technology (BHU), Varanasi, India), Sanjay Kumar Singh (Indian Institute of Technology (BHU), Varanasi, India)and K. K. Shukla (Indian Institute of Technology (BHU), Varanasi, India)
Copyright: 2016
Pages: 25
Source title:
Innovative Research in Attention Modeling and Computer Vision Applications
Source Author(s)/Editor(s): Rajarshi Pal (Institute for Development and Research in Banking Technology, India)
DOI: 10.4018/978-1-4666-8723-3.ch011
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Abstract
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.
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