Segmentation d'images par combinaison adaptative couleur-texture et classification de pixels. (Applications à la caractérisation de l'environnement de réception de signaux GNSS)

En segmentation d images, les informations de couleur et de texture sont très utilisées. Le premier apport de cette thèse se situe au niveau de l utilisation conjointe de ces deux sources d informations. Nous proposons alors une méthode de combinaison couleur/texture, adaptative et non paramétrique, qui consiste à combiner un (ou plus) gradient couleur et un (ou plus) gradient texture pour ensuite générer un gradient structurel utilisé comme image de potentiel dans l algorithme de croissance de régions par LPE. L originalité de notre méthode réside dans l étude de la dispersion d un nuage de point 3D dans l espace, en utilisant une étude comparative des valeurs propres obtenues par une analyse des composantes principales de la matrice de covariance de ce nuage de points. L approche de combinaison couleur/texture proposée est d abord testée sur deux bases d images, à savoir la base générique d images couleur de BERKELEY et la base d images de texture VISTEX. Cette thèse s inscrivant dans le cadre des projets ViLoc (RFC) et CAPLOC (PREDIT), le deuxième apport de celle-ci se situe au niveau de la caractérisation de l environnement de réception des signaux GNSS pour améliorer le calcul de la position d un mobile en milieu urbain. Dans ce cadre, nous proposons d exclure certains satellites (NLOS dont les signaux sont reçus par réflexion voir totalement bloqués par les obstacles environnants) dans le calcul de la position d un mobile. Deux approches de caractérisation, basées sur le traitement d images, sont alors proposées. La première approche consiste à appliquer la méthode de combinaison couleur/texture proposée sur deux bases d images réelles acquises en mobilité, à l aide d une caméra fisheye installée sur le toit du véhicule de laboratoire, suivie d une classification binaire permettant d obtenir les deux classes d intérêt ciel (signaux LOS) et non ciel (signaux NLOS). Afin de satisfaire la contrainte temps réel exigée par le projet CAPLOC, nous avons proposé une deuxième approche basée sur une simplification de l image couplée à une classification pixellaire adaptée. Le principe d exclusion des satellites NLOS permet d améliorer la précision de la position estimée, mais uniquement lorsque les satellites LOS (dont les signaux sont reçus de manière direct) sont géométriquement bien distribués dans l espace. Dans le but de prendre en compte cette connaissance relative à la distribution des satellites, et par conséquent, améliorer la précision de localisation, nous avons proposé une nouvelle stratégie pour l estimation de position, basée sur l exclusion des satellites NLOS (identifiés par le traitement d images), conditionnée par l information DOP, contenue dans les trames GPS.Color and texture are two main information used in image segmentation. The first contribution of this thesis focuses on the joint use of color and texture information by developing a robust and non parametric method combining color and texture gradients. The proposed color/texture combination allows defining a structural gradient that is used as potential image in watershed algorithm. The originality of the proposed method consists in studying a 3D points cloud generated by color and texture descriptors, followed by an eigenvalue analysis. The color/texture combination method is firstly tested and compared with well known methods in the literature, using two databases (generic BERKELEY database of color images and the VISTEX database of texture images). The applied part of the thesis is within ViLoc project (funded by RFC regional council) and CAPLOC project (funded by PREDIT). In this framework, the second contribution of the thesis concerns the characterization of the environment of GNSS signals reception. In this part, we aim to improve estimated position of a mobile in urban environment by excluding NLOS satellites (for which the signal is masked or received after reflections on obstacles surrounding the antenna environment). For that, we propose two approaches to characterize the environment of GNSS signals reception using image processing. The first one consists in applying the proposed color/texture combination on images acquired in mobility with a fisheye camera located on the roof of a vehicle and oriented toward the sky. The segmentation step is followed by a binary classification to extract two classes sky (LOS signals) and not sky (NLOS signals). The second approach is proposed in order to satisfy the real-time constraint required by the application. This approach is based on image simplification and adaptive pixel classification. The NLOS satellites exclusion principle is interesting, in terms of improving precision of position, when the LOS satellites (for which the signals are received directly) are well geometrically distributed in space. To take into account the knowledge of satellite distribution and then increase the precision of position, we propose a new strategy of position estimation, based on the exclusion of NLOS satellites (identified by the image processing step), conditioned by DOP information, which is provided by GPS data.BELFORT-UTBM-SEVENANS (900942101) / SudocSudocFranceF

A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans

In this paper, an efficient method for automatic and accurate detection of multiple objects from images using a region similarity measure is presented. This method involves the construction of two knowledge databases: The first one contains several distinctive textures of objects to be extracted. The second one is composed with textures representing background. Both databases are provided by some examples (training set) of images from which one wants to recognize objects. The proposed procedure starts by an initialization step during which the studied image is segmented into homogeneous regions. In order to separate the objects of interest from the image background, an evaluation of the similarity between the regions of the segmented image and those of the constructed knowledge databases is then performed. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. Experimental results obtained from the method applied to extract building roofs from orthophotoplans prove its robustness and performance over popular methods like K Nearest Neighbours (KNN) and Support Vector Machine (SVM)

Segmentation d'images couleur par combinaison LPE-régions/LPE-contours et fusion de régions. Application à la segmentation de toitures à partir d'orthophotoplans

D un point de vue général, les travaux de recherche de cette thèse s inscrivent dans le cadre d une approche globale quiconsiste à extraire des informations relatives aux toitures de bâtiments à partir de photos aériennes (orthophotoplans). L objectifétant de pouvoir reconnaître des toitures extraites d images aériennes en utilisant une base de connaissances, puisaffiner/déformer des modèles 3D générés automatiquement à partir de données géographiques. Pour cela, une premièreétape consiste tout d abord à partitionner l image aérienne en différentes régions d intérêt (pans de toiture, cheminées,chiens assis, fenêtres, etc.), c est la contribution de cette thèse.La méthodologie permettant d atteindre cet objectif est composée de trois étapes : (i) Une étape de simplification qui consisteà simplifier l image initiale avec un couple invariant/gradient approprié et optimisé pour l application. Pour cela, unesérie de tests permettant de choisir, d une part, l invariant colorimétrique le plus approprié parmi 24 invariants et, d autrepart, le meilleur gradient parmi 14 gradients issus de la littérature est réalisée. (ii) La deuxième étape comporte deux stratégiesde segmentation par LPE. L image simplifiée est segmentée d une part par une LPE-régions couplée à une stratégiede fusion de régions, et d autre part, par une LPE-contours. Le processus de fusion de régions intègre des critères defusion fondés sur des grandeurs radiométriques et géométriques adaptés aux particularités des orthophotoplans traités.Une technique de caractérisation 2D des arêtes de toitures par une analyse des segments est proposée afin de calculerl un des critères de fusion. (iii) La troisième étape consiste à combiner les avantages de chaque méthode dans un mêmeschéma de segmentation coopératif afin d aboutir à un résultat de segmentation fiable. Les tests ont été effectués sur unorthophotoplan contenant 100 toitures de complexité variée et évaluées avec le critère de VINET utilisant une segmentationde référence afin de prouver la robustesse et la fiabilité de l approche proposée. Une étape de comparaison permettantde situer les résultats obtenus via notre approche proposée par rapport à ceux obtenus pas les principales méthodes desegmentation de la littérature est finalement effectuée.The work presented in this thesis is developed in a global approach that consists in recognizing roofs extracted from aerialimages using a knowledge database, and bending out 3D models automatically generated from geographical data. Themain step presented in this thesis consists in segmenting roof images in different regions of interest in order to provideseveral measures of roofs (section of roofs, chimneys, roof light, etc).The method aimed at achieving this goal is composed of three principal steps: (i) A simplification step that consists insimplifying the image with an appropriate (optimized for the application) couple of invariant/gradient. For that, several testshave been performed to choose a suitable colorimetric invariant among a set of 24 invariants and define the best gradientamong 14 gradients (eight gray level gradients and six color gradients) of the literature. (ii) The second step is composedof two main treatments: On the one hand, the preliminary orthophotoplan segmentation is produced using the watershedregions applied on the simplified image. An efficient region merging strategy is then applied in order to deal with theover-segmentation problem. The regions merging procedure includes a merging criteria adapted to the orthophotoplanparticularities. In order to calculate one of the merging criteria, a 2D modeling of roof ridges strategy is proposed. Onthe other hand, the simplified image is segmented by the watershed lines. (iii) The third step consists in integrating bothsegmentation strategies by watershed algorithm into a single cooperative segmentation scheme to achieve satisfactorysegmentation results. Tests have been performed on an orthophotoplan containing 100 roofs with varying complexity andevaluated with VINET criteria using a ground truth image segmentation. Comparison results with five popular segmentationtechniques of the literature demonstrates the effectiveness and the reliability of the proposed approach.BELFORT-UTBM-SEVENANS (900942101) / SudocSudocFranceF

Segmentation d'images couleur par classification pixellaire et hiérarchie de partitions/ par Cyril Meurie

CAEN-BU Sciences et STAPS (141182103) / SudocSudocFranceF

Revisão da literatura sobre as concepções dos profissionais de saúde sobre o uso de drogas no Brasil: modelo biomédico, naturalizações e moralismos

Resumo Este estudo objetivou compreender as concepções dos profissionais de saúde no Brasil sobre o uso/abuso de drogas. Trata-se de revisão da literatura nas bases de dados MEDLINE, LILACS, IBECS e Scielo. A amostra final foi composta por 22 artigos, com os resultados apontando predominância de concepções morais, naturalizantes e pautadas pelo modelo biomédico, em detrimento de perspectivas psicossociais, socioculturais ou mesmo biopsicossociais. Ao se tratar de um problema multifacetado e complexo, as tentativas de respostas devem ir numa direção de amplitude e abrangência, pensando o uso de drogas para além de uma doença meramente, ou prática necessariamente negativa, mas compreendendo os aspectos físicos, psicológicos e também sociais que o perpassam. Na reversão desse cenário, coloca-se a necessidade de formação/capacitação na área, mas com reflexão sobre pressupostos e metodologias que fundamentam os processos formativos

Annotation tool designed for hazardous user behavior in guided mountain transport

IPAS 2018, 3rd IEEE International Conference on Image Processing, Applications and Systems, Sophia-Antipolis, FRANCE, 12-/12/2018 - 14/12/2018This paper proposes a semi-automatic ground truth annotation software designed for the specific needs of the EVEREST project. The purpose of this project is to build an annotated and anonymized video database, and use it to evaluate algorithms in the task of detecting hazardous behavior in guided mountain transport. To do so, a ground truth annotation tool that disposes designed specifically for the EVEREST project was needed. Ski lifts safety based on intelligent video systems is a niche domain which has not yet been explored in depth, which means no annotation tool suited for this task was available. That is why, we decided to develop a user-friendly and flexible tool to allows the semi-automatic annotation of events and faces (for privacy purposes). We looked at existing tracking algorithms, chose an implementation of TLD, and designed a new tracking algorithm that could be used when TLD isn't effective. This led to a simple, lightweight tracking algorithm that is more practical to use than the original CAMshift algorithm, and a user-friendly and flexible annotation tool that is well adapted to the specific task of annotating hazardous behavior in guided mountain transport

Superpixels for Image Processing and Computer Vision

International audienc

Graph-based ordering scheme for color image filtering

International audienceThis paper presents a graph-based ordering scheme of color vectors. A complete graph is defined over a filter window and its structure is analyzed to construct an ordering of color vectors. This graph-based ordering is constructed by finding a Hamiltonian path across the color vectors of a filter window by a two-step algorithm. The first step extracts, by decimating a minimum spanning tree, the extreme values of the color set. These extreme values are considered as the infimum and the supremum of the set of color vectors. The second step builds an ordering by constructing a Hamiltonian path among the vectors of color vectors, starting from the infimum and ending at the supremum. The properties of the proposed graph-based ordering of vectors are detailed. Several experiments are conducted to assess its filtering abilities for morphological and median filtering