Journal of Forensic Research

Detecting Cyclostationarity in Re-Captured LCD Screens

Abstract

Babak Mahdian, Adam Novozamsky and Stanislav Saic

It is easy to display a video or picture on an LCD screen and recapture it by using a camera to hide traces of digital image manipulation or fool an access system based on face recognition technique. In this paper, we show that humans do not have a good performance in detecting recaptured data from LCD screens. Hence, it is important to have methods capable of distinguishing between natural videos and pictures and those recaptured ones. In this paper, we show that, typically, recaptured images and videos from LCD screens exhibit detectable periodic patterns that are caused by regular sampling grid of the LCD monitor and aliasing. We develop our method using the theory of cyclostationarity and experimentally validate it. The term cyclostationarity refers to a special class of signals which exhibit periodicity in their statistics. Our method will be based on the fact that a cyclostationary signal has a frequency spectrum correlated with a shifted version of itself.