Paper Title
Intuitive Anti-Counterfeiting Detection Method For Video Surveillance Systems

Abstract
This study proposed an intuitive and quick detection method for use in crime prevention that effectively identified whether operating surveillance systems were being fed prerecorded images to deceive monitoring personnel. Based on chromaticity and spectral analysis conducted on prerecorded video displayed on a monitor and captured by a surveillance camera, it was accurately determined whether retrieved video was live or prerecorded. Using a neural network with image sequence analysis, the proposed anticounterfeit detection system achieved rapid detection with an accuracy rate higher than 99% and was easy to implement. Therefore, it could be easily installed into current video surveillance systems to curb deception. Keywords - Anti-counterfeiting System, Spatial Frequency Analysis, Color Space Analysis, Image Sequence Analysis, Probability Neural Network.