Statistical H.264 Double Compression Detection Method Based on DCT Coefficients

Abstract

With the 2019 Coronavirus pandemic, we have seen an increasing use of remote technologies such has remote identity verification. The authentication of the user identity is often performed through a biometric matching of a selfie and a video of an official identity document. In such a scenario, it is essential to verify the integrity of both the selfie and the video. In this article, we propose a method to detect double video compression in order to verify the video integrity. We will focus on the H.264 compression which is one of the mandatory video codecs in the WebRTC Requests For Comments. H.264 uses an integer approximation of the Discrete Cosine Transform (DCT). Our method focuses on the DCT coefficients to detect a double compression. The coefficients roughly follow a Laplacian distribution, we will show that the distribution parameters vary with respect to the quantisation parameter used to compress the video. We thus propose a statistical hypothesis test to determine whether or not a video has been compressed twice.

Keywords

• Video forensics
• double compression
• DCT
• H.264
• hypothesis testing