Ellipse detection through decomposition of circular arcs and line segments

International audienceIn this work we propose an efficient and original method for ellipse detection which relies on a recent contour representation based on arcs and line segments \cite{NguyenD11a}. The first step of such a detection is to locate ellipse candidate with a grouping process exploiting geometric properties of adjacent arcs and lines. Then, for each ellipse candidate we extract a compact and significant representation defined from the segment and arc extremities together with the arc middle points. This representation allows then a fast ellipse detection by using a simple least square technique. Finally some first comparisons with other robust approaches are proposed

Reconstruction et lissage de surfaces discrètes

Reconstruire une surface à partir des informations photométriques contenues dans une ou plusieurs images constitue un problème classique dans le domaine de la vision par ordinateur. Dans cette thèse, à travers un travail en collaboration avec des archéologues de l'IPGQ(Institut de Préhistoire et de Géologie du Quaternaire), nous nous sommes penchés sur le problème de reconstruction et d'extraction de paramètres de surfaces discrètes. Dans un premier temps, nous avons considéré le problème de reconstruction de surfaces à travers une approche discrète, en combinant les informations géométriques de la surface discrète que l'on reconstruit avec les informations photométriques contenues dans une ou plusieurs images. Nous avons pu définir une première méthode basée sur la propagation de contours discrets par niveaux d'iso-altitude. Même si cette approche a pu donner des résultats intéressants sur des images synthétiques, nous nous sommes orientés vers une autre approche beaucoup plus robuste. Cette deuxième méthode est basée sur la propagation de régions d'iso-altitude en considérant le contour d'iso-altitude de manière implicite. La reconstruction a pu montrer une grande résistance vis à vis du bruit et des informations photométriques. Cette méthode permet à travers les patchs de résoudre explicitement les ambiguïtés concaves/convexes lorsqu'une seule source lumineuse frontale est utilisée pour la reconstruction. De plus, étant donné que notre approche ne se base pas uniquement sur l'expression analytique de la fonction de réflectance (habituellement Lambertienne), nous avons pu effectuer la reconstruction d'objets réels spéculaires en considérant d'autres modèles de réflection tel que le modèle de Nayar. Enfin, nous avons pu montrer des résultats originaux permettant d'effectuer une reconstruction à partir de plusieurs dessins associés à plusieurs directions d'éclairage. Les résultats permettent d'envisager un concept original pour définir des formes à partir d'images associées à une surface imaginaire. Dans une deuxième partie, nous introduisons une nouvelle méthode réversible de lissage de surfaces discrètes. Cette méthode est basée sur l'estimation des caractéristiques du plan discret à partir d'un critère statistique et géométrique. Le critère statistique se base sur la répartition des différents types de surfels présents sur la surface, tandis que le critère géométrique est défini à partir des inégalités du plan discret. à partir de ces caractéristiques, nous définissons ensuite une surface à travers la projection des points discrets sur le plan tangent. Cette projection présente la propriété de transformer les points de Z3 dans R3 tout en étant réversible. La nouvelle surface Euclidienne résultante de cette transformation est à la fois utile pour l'extraction de paramètres géométriques et pour la visualisation sans aucune perte d'information par rapport à la surface discrète initiale.Shape reconstruction from shading informations contained in one or several images constitutes a classical problem in the field of computer vision. In this thesis, through a collaboration with archaeologists from the IPGQ (Institute of Prehistory and Quaternary Geology), we focus on the reconstruction and parameter extraction of discrete surfaces. First, we consider the problem of surface reconstruction using a discrete approach by combining geometric informations of the surface which is going to be reconstructed and photometric informations from one or several shading images. We have defined a new approach based on the propagation of discrete equal height contours. This approach gives good results on simple synthetic images, but we have chosen another approach in order to obtain more robustness on real images. This second method is based on the same idea through the propagation of equal height regions (called patch). The resulting reconstruction method gives robust results both on the point of view of photometric informations and noise. Moreover, it allows to explicitly solve the concave/convex ambiguity when only one light source direction (in the direction of the observer) is used for the reconstruction. Furthermore, since the reconstruction does not use the analytical expression of the reflectance map (usually Lambertian), the reconstruction was applied with other reflectance models such as the specular Nayar's model of reflectance. Finally, we have presented some original reconstructions obtained from several drawings associated with several light source directions. These results can offer new perspectives to define an intuitive way for shape modelling from shading images. In a second part, we introduce a new reversible method for discrete surface smoothing. This method is based on the estimation of the discrete plan characteristics using a statistical and geometrical criteria. The statistical criteria use the allocation of different types of discrete surface elements called surfel and the geometrical criteria is defined from the inequalities of the discrete plane. From the characteristics of the discrete tangent plane, a surface net is deduced by projecting the centers of voxels to the real tangent plane. This projection transforming the surface points from Z3 to R3 has the property to be reversible. Thus, it allows to obtain a new Euclidean surface net which can be used both for the extraction of geometrical parameters and for visualization

TKDetection: a software to detect and segment wood knots

TKDetection is a software proposing to segment the wood knots obtained from X-Ray Computed Tomography (CT) scanners. It implements algorithms combining tools of image analysis and discrete geometry, like connected component extraction, contour extraction or dominant point detection. TKDetection is the first free and open source software for the automatic knot segmentation. It is available on Github platform

Meaningful Thickness Detection on Polygonal Curve

International audienceThe notion of meaningful scale was recently introduced to detect the amount of noise present along a digital contour. It relies on the asymptotic properties of the maximal digital straight segment primitive. Even though very useful, the method is restricted to digital contour data and is not able to process other types of geometric data like disconnected set of points. In this work, we propose a solution to overcome this limitation. It exploits another primitive called the Blurred Segment which controls the straight segment recognition precision of disconnected sets of points. The resulting noise detection provides precise results and is also simpler to implement. A first application of contour smoothing demonstrates the efficiency of the proposed method. The algorithms can also be tested online

Curvature based corner detector for discrete, noisy and multi-scale contours

International audienceEstimating curvature on digital shapes is known to be a difficult problem even in high resolution images 10,19. Moreover the presence of noise contributes to the insta- bility of the estimators and limits their use in many computer vision applications like corner detection. Several recent curvature estimators 16,13,15, which come from the dis- crete geometry community, can now process damaged data and integrate the amount of noise in their analysis. In this paper, we propose a comparative evaluation of these estimators, testing their accuracy, efficiency, and robustness with respect to several type of degradations. We further compare the best one with the visual curvature proposed by Liu et al. 14, a recently published method from the computer vision community. We finally propose a novel corner detector, which is based on curvature estimation, and we provide a comprehensive set of experiments to compare it with many other classical cor- ner detectors. Our study shows that this corner detector has most of the time a better behavior than the others, while requiring only one parameter to take into account the noise level. It is also promising for multi-scale shape description

Extension des segments flous aux images en niveaux de gris pour l'extraction interactive de segments de droites

National audienceThe recognition of discrete straight segments is a significant topic in the field of discrete geometry and for many applications dealing with geometric feature extraction. It can be performed from noisy binary data using the concept of blurred segments [3,2]. However, to our best knowledge, these algorithms have never been defined to directly extract straight segments in gray level images. This article proposes a solution to extend the recognition by using gray level image information. Although initially intended to be implemented within a semi-automatic line selec- tion tool used in an interactive 3D modeling application, it also meets more general parameter extraction requirements.La reconnaissance de segments de droites discrètes est un problème significatif dans le domaine de la géométrie dis- crète et dans beaucoup d'applications d'extraction de pa- ramètres géométriques. L'utilisation du concept des seg- ments flous permet de traiter des images binaires brui- tées [3, 2]. Cependant ces algorithmes n'ont encore ja- mais été définis pour être utilisés directement dans des images en niveaux de gris. Nous proposons ici une solu- tion pour étendre la reconnaissance en utilisant les infor- mations des niveaux de gris d'une image. Bien qu'initia- lement conçu pour un outil semi-automatique de sélection de droites dans une application de modélisation 3d interac- tive, l'approche proposée répond aussi à des besoins plus généraux liés à l'extraction de paramètres

Curvature Estimation along Noisy Digital Contours by Approximate Global Optimization

International audienceIn this paper we introduce a new curvature estimator along digital contours, that we called Global Min-Curvature estimator (GMC). As opposed to previous curvature estimators, it considers all the possible shapes that are digitized as this contour, and selects the most probable one with a global optimization approach. The GMC estimator exploits the geometric properties of digital contours by using local bounds on tangent directions defined by the maximal digital straight segments. The estimator is then adapted to noisy contours by replacing maximal segments with maximal blurred digital straight segments. Experiments on perfect and damaged digital contours are performed and in both cases, comparisons with other existing methods are presented

Intuitive Shape Modeling by Shading Design

Shading has a great impact to the human perception of 3D objects. Thus, in order to create or to deform a 3D object, it seems natural to manipulate its perceived shading. This paper presents a new solution for the software implementation of this idea. Our approach is based on the ability of a user to coarsely draw a shading, under different lighting directions. With this intuitive process, users can create or edit a height field (locally or globally), that will correspond to the drawn shading values. Moreover, we present the possibility to edit the shading intensity by means of a specular reflectance model

IPOL: a new journal for fully reproducible research; analysis of four years development

International audienceAfter four years of development of the Image Processing On Line journal (IPOL), this article presents a first analysis and overview of its scientific and technical development. The main issues met and overcome from the beginning of the journal are described with a focus on the purpose of the journal to establish a state of the art on the main Image Processing topics. The evolution of the online demonstration is also presented with a first analysis of author/publisher criticism, which led to a proposal for a new modular architecture of its demo system

Complementary Experiments of the Thick Line Segment Detection Algorithm: Evaluation of ADS and ATC Concepts

This document presents complementary experiments on the published algorithm of Thick Line Segment Detection with Fast Directional Tracking. The main paper is actually published at ICIAP 2019 [2]. First tests compare the performance of the detector with and without adaptive directional scans (ADS) and assigned thickness control (ATC). On the detector without ADS, the ne tracking step must be performed twice to get less risk of growing blurred segment escape from the scan strip