Due to the widespread use of the JPEG format, non-aligned double JPEG (NA-DJPEG) compression is very common in image tampering. Therefore, non-aligned double JPEG compression detection has attracted significant attention in digital forensics in recent years. In most of the previous detection algorithms, grayscale images are used directly, or color images are first converted into grayscale images and then processed. However, it is worth noting that most tampered images are color images. To make full use of the color information in images, a detection algorithm, which uses color images directly, is put forward in this paper. The algorithm based on refined Markov in quaternion discrete cosine transform (QDCT) domain is proposed for NA-DJPEG compression detection. Firstly, color information of a given JPEG image is extracted from blocked images to construct quaternion, and then block image QDCT coefficient matrices, including amplitude and three angles (\(\psi \), \(\phi \), and \(\theta \)) can be obtained. Secondly, the refined Markov features are generated from the transition probability matrix in the corresponding refinement process. Our proposed refinement method not only reduces redundant features but also makes the acquired features more efficient in detection. Therefore, the refined Markov features can not only capture the intra-block correlation between block QDCT coefficients but also improve computing efficiency in real-time. Finally, support vector machine (SVM) method is employed for NA-DJPEG compression detection. The experiment results demonstrate that the proposed algorithm not only make use of color information of images, but also can achieve better detection performance with small size images (i.e., \(64 \times 64\)) outperforming state-of-the-art detection methods tested on the same dataset.

中文翻译：

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基于QDCT域中精确马尔可夫特征的非对齐双JPEG压缩检测

由于JPEG格式的广泛使用，非对齐双JPEG（NA-DJPEG）压缩在图像篡改中非常普遍。因此，近年来，未对准的双重JPEG压缩检测在数字取证领域引起了极大的关注。在大多数以前的检测算法中，直接使用灰度图像，或者将彩色图像首先转换为灰度图像，然后进行处理。但是，值得注意的是，大多数被篡改的图像都是彩色图像。为了充分利用图像中的颜色信息，提出了一种直接使用彩色图像的检测算法。提出了一种基于改进马尔可夫四元数离散余弦变换（QDCT）域的NA-DJPEG压缩检测算法。首先，可以获得\（\ psi \），\（\ phi \）和\（\ theta \））。其次，在相应的细化过程中，由转变概率矩阵生成细化的马尔可夫特征。我们提出的改进方法不仅减少了冗余特征，而且使获得的特征更有效地检测。因此，改进的马尔可夫特征不仅可以捕获块QDCT系数之间的块内相关性，而且可以实时提高计算效率。最后，采用支持向量机（SVM）方法进行NA-DJPEG压缩检测。实验结果表明，该算法不仅可以利用图像的颜色信息，而且对于小尺寸图像（例如，\（64 \ times 64 \））优于在同一数据集上测试的最新检测方法。