Researchers at Punjab University have developed a sensor pattern noise based method to detect forged videos where one video is copied onto a different video.
The digital age has been slowly spreading with increasing surveillance and other autonomous systems replacing the old manually operated ones. CCTV cameras, head/ vehicle mounted cameras and devices like Go-pro enable live recording of events as they unfold. The videos generated have already had a huge impact on law enforcement, providing clues and evidence to solving a case. They have also assisted other professions like journalism, politics and even military and intelligence operations. However, the main concern with video based evidence is their accuracy. Increasingly, fake videos and morphed pictures have been used for political gains or to mislead a jury. Assisted by the social media platforms where videos can go viral, having huge reach, such forged videos can have a huge impact and as such it has become crucial to detect any changes and forgeries made to video, before making them public.
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