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Detection of inconsistencies of double JPEG artefacts across different imageregions is often used to detect local image manipulations, like image splicing,and to localize them. In this paper, we move one step further, proposing anend-to-end system that, in addition to detecting and localizing splicedregions, can also distinguish regions coming from different donor images. Weassume that both the spliced regions and the background image have undergone adouble JPEG compression, and use a local estimate of the primary quantizationmatrix to distinguish between spliced regions taken from different sources. Todo so, we cluster the image blocks according to the estimated primaryquantization matrix and refine the result by means of morphologicalreconstruction. The proposed method can work in a wide variety of settingsincluding aligned and non-aligned double JPEG compression, and regardless ofwhether the second compression is stronger or weaker than the first one. Wevalidated the proposed approach by means of extensive experiments showing itssuperior performance with respect to baseline methods working in similarconditions.

Image Splicing Detection, Localization and Attribution via JPEG Primary Quantization Matrix Estimation and Clustering