Publications




Local JPEG Grid Detector via Blocking Artifacts, a Forgery Detection Tool

IPOL, avril 2020

Image JPEG compression leaves blocking artifact traces. This paper describes an algorithm that exploits those traces to locally recover the grid embedded in the image by the JPEG compression. The algorithm returns a list of grids associated with different parts of the image. The method uses Chen and Hsu’s cross-difference to reveal the artifacts. Then, an a contrario validation step according to Desolneux, Moisan and Morel’s theory delivers for each detected grid a Number of False Alarms (NFA) which tells how unlikely it is that the detection is due to chance. The only parameter is the step size of the windows used, which represents the exhaustiveness of the method. The application to image forgery detection is twofold: first, the presence of discrepant JPEG grids with low NFA is a strong forgery cue; second, knowledge of the grid is anyway required for further JPEG forensic analysis.
   


Détection de grille JPEG par compression simulée

GRETSI, août 2019

La rétro-ingénierie est un outil efficace pour détecter les falsifications d’images. Nous proposons une méthode simple et fiable pour détecter la compression JPEG et la position de sa grille, et la comparons à l’état de l’art. La méthode peut être utilisée afin de déterminer si une image a été rognée, ce qui est souvent le premier indice de falsification.
   


JPEG Grid Detection based on the Number of DCT Zeros and its Application to Automatic and Localized Forgery Detection

CVPR Workshop, juin 2019

This work proposes a novel method for detecting JPEG compression, as well as its grid origin, based on counting the number of zeros in the DCT of 8 × 8 blocks. When applied locally, the same method can be used to detect grid alignment abnormalities. It therefore detects local image forgeries such as copy-move. The algorithm includes a statistical validation step which gives theoretical guarantees on the number of false alarms and provides secure guarantees for tampering detection. The performance of the proposed method is illustrated with both quantitative and visual results from well-known image databases and comparisons with state of the art methods.
   


Parallel-beam ROI reconstruction with differentiated backprojection and angularly subsampled complementary sinograms

Fifth International Conference on Image Formation in X-Ray Computed Tomography, mai 2018

Recently, we introduced a parallel-beam two-pass analytical reconstruction that allows truncation to be accounted for in the image domain rather than the projection domain. In particular, we showed that backprojection of a vastly angularly undersampled sinogram of un-truncated data could be used to extrapolate the backprojection of a finely sampled, fully truncated sinogram of the same object to perform more accurate region-of-interest (ROI) imaging. The same extrapolation idea can be performed using differentiated backprojection (DBP). The goal of this study is to give a general DBP-based formula when reconstructing a finite set of projections in parallel geometry. We discuss the discretization of this formula, in particular when the image grid size is large with respect to the number of projections, and we show how it can be applied to our extrapolation problem.
 


Automatic JPEG Grid Detection with Controlled False Alarms, and Its Image Forensic Applications

IEEE MIPR, avril 2018

With the progress of image manipulation tools and the proliferation of fake news and images posted online on social networks, automatic identification of fake content is becoming indispensable. Lossy image compression leaves traces which can be used to recover the history of an image and to help decide about its authenticity. We propose a new JPEG grid detection algorithm. This operation is the first step of many forensic, anti-forensic, and deblocking algorithms. Our analysis is based on the detection of the blocking artifacts and is global and local at the same time. It retrieves the origin of the JPEG grid in all image regions and detects suspicious discrepancies. Our work is based on the a-contrario framework which reins in the over-detections caused by multiple testing. It also yields a Number of False Alarms (NFA) which gives extremely secure guarantees for tampering detection. We demonstrate the performance of the proposed method with both quantitative and visual results from well-known image databases.