Double JPEG Compression Detection by Exploring the Correlations in DCT Domain
This work addresses image forgery detection for digital forensics, but it is incremental as it builds on existing methods with specific improvements.
The paper tackled the problem of detecting double JPEG compression, which can indicate image tampering, by proposing an algorithm that analyzes correlations in the DCT domain and achieved comparable performance in experiments.
In the field of digital image processing, JPEG image compression technique has been widely applied. And numerous image processing software suppose this. It is likely for the images undergoing double JPEG compression to be tampered. Therefore, double JPEG compression detection schemes can provide an important clue for image forgery detection. In this paper, we propose an effective algorithm to detect double JPEG compression with different quality factors. Firstly, the quantized DCT coefficients with same frequency are extracted to build the new data matrices. Then, considering the direction effect on the correlation between the adjacent positions in DCT domain, twelve kinds of high-pass filter templates with different directions are executed and the translation probability matrix is calculated for each filtered data. Furthermore, principal component analysis and support vector machine technique are applied to reduce the feature dimension and train a classifier, respectively. Experimental results have demonstrated that the proposed method is effective and has comparable performance.