Pooled Steganalysis in JPEG: how to deal with the spreading strategy?

International audienceIn image pooled steganalysis, a steganalyst, Eve, aims to detect if a set of images sent by a steganographer, Alice, to a receiver, Bob, contains a hidden message. We can reasonably assess that the steganalyst does not know the strategy used to spread the payload across images. To the best of our knowledge, in this case, the most appropriate solution for pooled steganalysis is to use a Single-Image Detector (SID) to estimate/quantify if an image is cover or stego, and to average the scores obtained on the set of images. In such a scenario, where Eve does not know the spreading strategies, we experimentally show that if Eve can discriminate among few well-known spreading strategies, she can improve her steganalysis performances compared to a simple averaging or maximum pooled approach. Our discriminative approach allows obtaining steganalysis efficiencies comparable to those obtained by a clairvoyant, Eve, who knows the Alice spreading strategy. Another interesting observation is that DeLS spreading strategy behaves really better than all the other spreading strategies. Those observations results in the experimentation with six different spreading strategies made on Jpeg images with J-UNIWARD, a state-of-the-art Single-Image-Detector, and a dis-criminative architecture that is invariant to the individual payload in each image, invariant to the size of the analyzed set of images, and build on a binary detector (for the pooling) that is able to deal with various spreading strategies

Automatic identification of cell files in light microscopic images of conifer wood

International audienceIn this paper, we present an automatic method to recognize cell files in light microscopic images of conifer wood. This original method is decomposed into three steps: the segmentation step which extracts some anatomical structures in the image, the classification step which identifies in these structures the interesting cells, and the cell files recognition step. Some preliminary results obtained on several species of conifers are presented and analyzed

JPEG2000-Based Data Hiding to Synchronously Unify Disparate Facial Data for Scalable 3D Visualization

International audienceWe present a scalable encoding strategy for the 3D facial data in various bandwidth scenarios. The scalability, needed to cater diverse clients, is achieved through the multiresolution characteristic of JPEG2000. The disparate 3D facial data is synchronously unified by the application of data hiding wherein the 2.5D facial model is embedded in the corresponding 2D texture in the discrete wavelet transform (DWT) domain. The unified file conforms to the JPEG2000 standard and thus no novel format is introduced. The method is effective and has the potential to be applied in videosurveillance and videoconference applications

3D Facial Visualization Through Adaptive Spread Spectrum Synchronous Scalable (A4S) Data Hiding

International audienceAn adaptive spread spectrum synchronous scalable(A4S) data hiding strategy is being put forward to integrate the disparate 3D facial visualization data, into a single JPEG2000 format file with the aim to cater diverse clients in various bandwidth scenarios. The method is both robust and imperceptible in the sense that the robustness of the spread spectrum (SS) is coupled with the removable embedding that ensures highest possible visualization quality. The SS embedding of the DWT-domain 2.5D facial model is carried out in the transform domain YCrCb components, of the 2D texture, from the coding stream of JPEG2000 codec just after the DWT stage. High depth map quality is ensured through the adaptation of synchronization during embedding that would exclude some highest frequency subbands. The results show that the method can be exploited for video-surveillance and video-conference applications

Le cerveau en quatre dimensions

National audienceLes images médicales en trois dimensions restent délicates à interpréter, notamment pour suivre un patient dans le temps. Et si l'ordinateur venait aider à analyser ce que la machine a déjà aidé à produire? Les informaticiens font appel à la géométrie et à la physique pour résoudre un solide problème mathématique. Cas pratique, le cerveau

How to build an average model when samples are variably incomplete? Application to fossil data

International audienceIn paleontology, incomplete samples with small or large missing parts are frequently encountered. For example,dental crowns, which are widely studied in paleontology because of their potential interest in taxonomic and phylogenetic analyses, are nearly systematically affected by a variable degree of wear that alters considerably their shape. It is then difficult to compute a significant reference surface model based on classical methods which are used to build atlases from set of samples. In this paper, we present a general approach to deal with the problem of estimating an average model from a set of incomplete samples. Our method is based on a state-of-the-art non-rigid surface registration algorithm. In a first step, we detect missing parts which allows one to focus only on the common parts to get an accurate registration result. In a second step, we try to build average model of the missing parts by using information which is available in a subset of the samples. We specifically apply our method on teeth, and more precisely on the surface in between dentine and enamel issues (EDJ). We investigate the robustness and accuracy properties of the methods on a set of artificial samples representing a high degree of incompleteness. We compare the reconstructed complete shape to a ground-truth dataset. We then show some results on real data