Detection of Double Compression With the Same Coding Parameters Based on Quality Degradation Mechanism Analysis

Detection of double compression with the same coding parameters is a very challenging problem in video forensics, since traces of recompression operations are extremely slight in this case. To solve this problem, we first analyze degradation mechanisms during recompression. It is observed that the video quality tends to become nearly unchanged after multiple recompressions with the same coding parameters. The degree of quality degradation is used to distinguish single and double compressed videos. This property can be described using the convergent tendency of video data to unchanged states after continuous recompressions. For MPEG videos, statistical features of rounding and truncation errors are extracted from the intra-coding process while macroblock-mode based features are obtained from the inter-coding process. The final feature is generated by concatenating these two sets of features to provide robust detection capability. Then, extracted features are fed to the SVM classifier to obtain the final detection result. In addition, aforementioned features are modified and extended to detect double compression on H.264 videos based on the unique coding techniques developed in the H.264 standard, such as intra-prediction. Several public available YUV sequences are used to construct double compression databases with three popular coding standards, including MPEG-2, MPEG-4, and H.264. In experiments, the proposed method outperforms several state-of-the-art methods for different compression qualities and rate control schemes. Experimental results demonstrate the proposed method has more robust detection capability of double compression under various encoding configurations.