Identification of aliasing-based patterns in re-captured LCD screens
Babak Mahdian, Adam Novozámský, Stanislav Saic · 2015
In this paper we address the problem of identification of pictures and videos re-captured from LCD screens. We show that they often exhibit detectable periodic patterns that are caused by regular sampling grid of LCD screen and aliasing. We develop a method capable of detecting these patterns by using the theory of cyclostationarity. The term cyclostationarity refers to a special class of signals which exhibit periodicity in their statistics. Such signals have a frequency spectrum correlated with a shifted version of itself. Experimental results quantifying the performance of the developed method are also shown.