Region based variational approach for the segmentation textured sonar images

We propose a new region-based segmentation of textured sonar images with respect to seafloor types. We characterize sea-floor types by a set of empirical distributions estimated on texture responses to a set of different filters and we introduce a novel similarity measure between sonar textures in this attribute space. Our similarity measure is defined as a weighted sum of Kullback-Leibler divergences between texture features. The texture similarity measure weight setting is twofold : first we weight each filter, according to its discrimination power, the computation of these weights are issued from the margin maximization criterion. Second, we add an additional weighting, evaluated as an angular distance between the incidence angles of the compared texture samples, to cope with the problem related to the sonar image acquisition process that leads to a variability of the backscattered (BS) value and the texture aspect with the incidence angle range. Our segmentation method is stated as the minimization of a region-based functional that involves the similarity between region texture based statistics and prototype ones and a regularization term that imposes smoothness and regularity on region boundaries. The proposed approach is implemented using level-set methods, and the functional minimization is done using shape derivative tools.Nous proposons une nouvelle méthode formulée au niveau région pour la segmentation texturale d’images sonar haute résolution. Nous caractérisons les différents types de fonds marins par des descripteurs de texture sous forme de distributions de leurs réponses à un ensemble de filtres, estimées sur la globalité des régions et nous définissons une nouvelle mesure de similarité adaptée à la discrimination entre fonds marins dans l’espace de ces descripteurs. Notre mesure de similarité est une somme doublement pondérée de divergences de Kullback-Leibler entre les descripteurs de textures : la première pondération permet la sélection des filtres les plus pertinents pour la discrimination entre textures et la deuxième pondération est angulaire et elle permet de tenir compte de la variation des descripteurs de texture en fonction des angles d’incidence. La méthode de segmentation est formulée dans un cadre variationnel. La fonctionnelle d’énergie associée fait intervenir deux termes. Le premier est un terme qui évalue l’homogénéité des régions selon la mesure de similarité pondérée entre les statistiques estimées sur les différentes régions de l’image et les prototypes relatifs aux différents types de fonds marins. Le deuxième terme contraint la régularité des frontières entre régions. La minimisation de la fonctionnelle est effectuée par descente du gradient et exploite les outils de dérivation de forme et la méthode est implantée selon la technique des ensembles de niveaux

Mécanismes des processus interprétatifs conscients et inconscients

When we perceive a word, a picture or a sound, we do not access an ‘objective’ representation of them. Rather we gain immediate access to a subjective interpretation. This interpretation reflects the combination of our prior knowledge about the world with data sampled in the environment. An interesting issue is to understand how we deal with inconsistencies between our prior knowledge and the data from the environment. During this PhD, responses to inconsistencies both in the environment and in subjects’ own behavior were explored. The first series of studies address how subjects process regularities in the environment and how these processes relate to conscious access. To do so, two levels of auditory regularities were studied in epileptic patients implanted with intracranial electrodes. In a second experiment, we used a paradigm derived from the Stroop task to test responses to frequent conscious or unconscious conflicts. Behavioral measures and scalp EEG were used to assess changes in subjects’ strategy when processing trials conflicting with current expectations. In the second series of studies, we analyzed how subjects adapt their interpretations when confronted with inconsistencies in their own behavior, using the framework of cognitive dissonance. The implication of explicit memory was tested in a behavioral experiment and in an fMRI study. The results of these four studies are discussed around two main issues. First, these results highlight the existence of processes which rely on conscious stimuli but are not conscious themselves. Second, we examine what could explain our tendency to constantly seek consistency both in the external world and in our own behavior.Lorsqu’une représentation accède à la conscience, ce n’est pas simplement une représentation « objective », mais plutôt une interprétation subjective. Cette interprétation reflète la combinaison de nos connaissances sur le monde avec les données de notre environnement. Il est intéressant de comprendre comment ces interprétations se modifient lorsque l’on est confronté à des incohérences entre nos connaissances et les données. Dans cette thèse, nous avons étudié ces incohérences dans l’environnement et dans le comportement des individus.Dans une première série d’études, nous avons étudié l’apprentissage de régularités dans l’environnement ainsi que les relations entre ce processus et la conscience d’accès. La première étude porte sur les réponses cérébrales associées à la détection de régularités auditives chez des patients épileptiques implantés. La seconde porte sur la mise en place de stratégies lorsque l’on est confronté à de fréquents conflits, conscients ou non. Dans une seconde série d’études, nous avons étudié comment les sujets traitent les incohérences dans leur propre comportement, dans le cadre de la théorie de la dissonance cognitive, en utilisant le paradigme du choix libre. Nous avons identifié un rôle crucial de la mémoire grâce à une étude comportementale et une étude en IRM fonctionnelle.Les résultats de ces quatre études sont discutés dans ce manuscrit autour de deux questions clés. Tout d’abord, ces résultats mettent en évidence l’existence de processus utilisant des stimuli conscients, mais qui ne sont pas conscients eux-mêmes. Ensuite, nous discutons pourquoi l’on tend à chercher de la cohérence, dans notre environnement et dans notre comportement

ACOUSTIC OBSTACLE DETECTION FOR SAFE AUV SURFACING

International audienceWe propose an automatic sea surface object detection from forward lookingsonar images. The considered sea surface obstacles are man-made objects: buoys, boats,ships (motorboats or sailboats). Their acoustic signature varies according to their typeand state (fixed or moving).The proposed detection scheme is hierarchical in order to manage the various targetsignatures. The first step consists in detecting stationary self noise from ships. In case ofdetection, the strong-intensity strip corresponding to the ship direction is removed toavoid ship noise disturbance during other target detection processes. The next stepconsists in detecting the other types of obstacles. It is based on an adaptive CFAR(Constant False Alarm Rate) thresholding. The final step consists in analyzing the areaaround every detected position in order to state that this latter is a reliable obstacle andnot a wake signature. Promising results are obtained using real data collected at sea withvarious objects and scenarios

Automatic Sea-Surface Obstacle Detection andTracking in Forward-Looking SonarImage Sequences

International audienceAutomatic sea-surface object detection and trackingfor safe autonomous underwater vehicle and submarine surfacingis a critical issue in relation to the accidents reported in the lastdecades. Here, we propose an efficient tool to detect and tracksea-surface obstacles by processing forward-looking sonar images.The proposed method can detect either still or moving objects withand without wake. For each image sequence, a sequential procedureis proposed to detect various obstacle signatures. Then, targetpositions and velocities are estimated in Cartesian coordinatesusing the debiased converted measurement Kalman filter and thejoint probabilistic data association filter. Detection and trackingstages exchange information in order to reduce the number of falsealarms. Promising results are obtained using real data collected atsea with various objects and scenarios

AUTOMATIC SPATIAL CLUSTERING AND TRACKING OF SEASURFACE OBSTACLES IN FORWARD LOOKING SONAR IMAGES

International audienceThis paper presents an automatic sea surface object clustering and tracking inforward looking sonar images. The considered sea surface obstacles are man-madeobjects: buoys, boats, ships (motorboats or sailboats). Their acoustic signature variesaccording to their type and state (fixed or moving).The proposed method detects the various target signatures. Then detections are gatheredinto clusters using an automatic and adaptive clustering method based on the DelaunayTriangulation. After the clustering stage, isolated detections are rejected and theremaining clusters are classified into two types: clusters including wake or not. Thisclassification is based on the shape eccentricity feature. Then, according to the clustertype, the obstacle position is extracted to be used for tracking. For clusters without wake,the obstacle position is the centroid of the cluster but for clusters including wake, wakeextremities are set as possible vessel position.Finally, obstacle tracking is carried out in Cartesian coordinates using the DebiasedConverted Measurement Kalman filter and the Joint Probabilistic Data Association Filter.Promising results are obtained using real data collected at sea with various objects andscenarios

Variational region-based segmentation using multiple texture statistics

International audienceThis paper investigates variational region-level criterion for supervised and unsupervised texturebased image segmentation. The focus is given to the demonstration of the effectiveness and robustness of this region-based formulation compared to most common variational approaches. The main contributions of this global criterion are twofold. First, the proposed methods circumvent a major problem related to classical texture based segmentation approaches. Existing methods, even if they use different and various texture features, are mainly stated as the optimization of a criterion evaluating punctual pixel likelihoods or similarity measure computed within local neighborhood. The former approaches require sufficient dissimilarity between used feature statistics. The latter involve an additional limitation which is the choice of the neighborhood size and shape. These two parameters and especially the neighborhood size significantly influence the classification performances: the neighborhood must be large enough to capture texture structures and small enough to warrant segmentation accuracy. These parameters are often set experimentally. To address these limitations, the proposed methods are stated at the region-level, both for stating the overall variational criterion and the observation-driven texture criterion. It resorts to an energy criterion on image regions: image regions are characterized by non-parametric distributions of their responses to a set of filters. In supervised case the segmentation algorithm consists in the minimization of a similarity measure between regions features and texture prototypes and a boundary based functional that imposes smoothness and regularity on region boundaries. In unsupervised case, the segmentation consists in the maximization of the dissimilarity between regions. The proposed similarity-based criteria are generic and permit optimally fusing various types of texture features. It is defined as a weighted sum of Kullback-Leibler divergences between feature distributions. The optimization of the proposed variational criteria is carried out using a level-set formulation. The effectiveness and the robustness of this formulation at region-level, compared to classical active contour methods, are evaluated for various Brodatz and natural images

Can application and transfer of strategy be observed in low visibility condition?

International audienceIt has been long assumed that cognitive control processes can only be applied on consciously visible stimuli, but empirical evidence is contradictory. In the present study, we investigated strategic adaptation to conflict both in unmasked and in low-visibility masked trials. Using a paradigm derived from the Stroop task, we studied the application of strategies, but also the transfer of a strategy developed in unmasked trials to masked trials, and the trial-to-trial dynamics of strategic processing. In unmasked trials, we found evidence of strategic adaptation to conflict, both in reaction times and in ERPs (N2 and P300). In masked trials we found no evidence of behavioral adaptation to conflict, but a modulation of the P300 was present in masked trials included in unmasked blocks, suggesting the existence of a transfer of strategy. Finally, trial-to-trial analyses in unmasked trials revealed a pattern suggestive of dynamic subjective adherence to the instructed strategy

Fast marching and acoustic descriptors based method for fish proportion interpolation

International audienceWe propose a new method for the estimation of fish abundance from both acoustic data and some trawl hauls catches. In this work, we operate at a global level and we aim at estimating fish abundance from these images and not to identify the species of each school. We associate each trawl catch to the nearest acoustic image and we describe each image by a set of global statistical distributions estimated on it and related to each school parameters. Then, we use the fast marching algorithm, a front propagation based scheme to define a region of interest around each trawl associated image. The fast marching algorithm propagates each front initialized on the image associated to the trawl samples with a velocity proportional to the distance between the trawl image acoustic features and those of the image for which we want to estimate the fish abundance. Finally, the fish abundance of each image is estimated as a weighted sum of the abundances associated to each trawl. The weights are estimated from the propagation time given by the fast marching algorithm. The method is experimented on real and synthetic data

Multi-resolution eddy detection from ocean color and sea surface temperature images

International audienc