The abundance of digital video forms a potential piece of evidence in courtrooms.
Augmenting subjective assessment of digital video evidence by an automated objective
assessment helps increase the accuracy of deciding whether or not to admit the digital video
as legal evidence. This paper examines the authenticity of digital video evidence and in
particular it proposes a machine learning approach to detecting frame deletion. A number of
discriminative features are extracted from the video bit stream and its reconstructed images …