Coarse to fine : toward an intelligent 3D acquisition system

International audienceThe 3D acquisition-compression-processing chain is , most of the time , sequenced into independent stages. As resulting , a large amount of 3D points are acquired whatever the geometry of the object and the processing to be done in further steps. It appears , particularly in mechanical part 3D modeling and in CAD , that the acquisition of such an amount of data is not always mandatory. We propose a method aiming at minimizing the number of 3D points to be acquired with respect to the local geometry of the part and therefore to compress the cloud of points during the acquisition stage. The method we propose is based on a new coarse to fine approach in which from a coarse set of 2D points associated to the local normals the 3D object model is segmented into a combination of primitives. The obtained model is enriched where it is needed with new points and a new primitive extraction stage is performed in the refined regions. This is done until a given precision of the reconstructed object is attained. It is noticeable that contrary to other studies we do not work on a meshed model but directly on the data provided by the scanning device

A coarse to fine 3D acquisition system

International audienceThe 3D chain (acquisition-processing-compression) is , most of the time , sequenced into several steps. Such approaches result into an one-dense acquisition of 3D points. In large scope of applications , the first processing step consists in simplifying the data. In this paper , we propose a coarse to fine acquisition system which permits to obtain simplified data directly from the acquisition. By calculating some complementary information from 2D images , such as 3D normals , multiple homogeneous regions will be segmented and affected to a given primitive class. Contrary to other studies , the whole process is not based on a mesh. The obtained model is simplified directly from the 2D data acquired by a 3D scanner

Détection de primitives par une approche discrète et non linéaire (application à la détection et la caractérisation de points d'intérêt dans les maillages 3D)

Ce manuscrit est dédié à la détection et la caractérisation de points d'intérêt dans les maillages. Nous montrons tout d'abord les limitations de la mesure de courbure sur des contours francs, mesure habituellement utilisée dans le domaine de l'analyse de maillages. Nous présentons ensuite une généralisation de l'opérateur SUSAN pour les maillages, nommé SUSAN-3D. La mesure de saillance proposée quantifie les variations locales de la surface et classe directement les points analysés en cinq catégories : saillant, crête, plat, vallée et creux. Les maillages considérés sont à variété uniforme avec ou sans bords et peuvent être réguliers ou irréguliers, denses ou non et bruités ou non. Nous étudions ensuite les performances de SUSAN-3D en les comparant à celles de deux opérateurs de courbure : l'opérateur de Meyer et l'opérateur de Stokely. Deux méthodes de comparaison des mesures de saillance et courbure sont proposées et utilisées sur deux types d objets : des sphères et des cubes. Les sphères permettent l'étude de la précision sur des surfaces différentiables et les cubes sur deux types de contours non-différentiables : les arêtes et les coins. Nous montrons au travers de ces études les avantages de notre méthode qui sont une forte répétabilité de la mesure, une faible sensibilité au bruit et la capacité d'analyser les surfaces peu denses. Enfin, nous présentons une extension multi-échelle et une automatisation de la détermination des échelles d'analyse qui font de SUSAN-3D un opérateur générique et autonome d analyse et de caractérisation pour les maillagesThis manuscript is dedicated to the detection and caracterization of interest points for 3D meshes. First of all, we show the limitations of the curvature measure on sharp edges, the measure usually used for the analysis of meshes. Then, we present a generalization of the SUSAN operator for meshes, named SUSAN-3D. The saliency measure proposed quantify the local variation of the surface and classify directly the analysed vertices in five classes: salient, crest, flat, valley and cavity. The meshes under consideration are manifolds and can be closed or non-closed, regulars or irregulars, dense or not and noised or not. The accuracy of the SUSAN-3D operator is compared to two curvature operators: the Meyer's operator and the Stokely's operator. Two comparison methods of saliency and curvature measures are described and used on two types of objects: spheres and cubes. The spheres allow the study of the accuracy for differentiable surfaces and the cubes for two types of sharp edges: crests and corners. Through these studies, we show the benefits of our method that are a strong repeatability of the measure, high robustness to noise and capacity to analyse non dense meshes. Finally, we present a multi-scale scheme and automation of the determination of the analysis scales that allow SUSAN-3D to be a general and autonomous operator for the analysis and caracterization of meshesDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

A 3D scanner for transparent glass

Many practical tasks in industry, such as automatic inspection or robot vision, often require the scanning of three-dimensional shapes by use of non-contact techniques. However, few methods have been proposed to measure three-dimensional shapes of transparent objects because of the difficulty of dealing with transparency and specularity of the surface. This paper presents a 3D scanner for transparent glass objects based on Scanning From Heating (SFH), a new method that makes use of local surface heating and thermal imaging

A combined three-dimensional digitisation and subsurface defect detection data using active infrared thermography

International audienceIn recent years, NonDestructive Testing (NDT) systems have been upgraded with three-dimensional information. Indeed, combine the three-dimensional and thermal information allows a more meaningful analysis. In the literature, the data for NDT and three-dimensional (3D) reconstruction analysis are commonly acquired from independent systems. However, the use of two such systems leads to error analysis during the data registration. In an attempt to overcome such problems, we propose a single system based on active thermography approach using heat point-source stimulation to get the 3D digitization as well as subsurface defect detection. The experiments are conducted on steel and aluminum objects, and a combined 3D / thermal-information is presented

Three-dimensional scanning of specular and diffuse metallic surfaces using an infrared technique

For the past two decades, the need for three-dimensional (3-D) scanning of industrial objects has increased significantly and many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non-cooperative surfaces, such as transparent or specular surfaces. To address highly reflective metallic surfaces, we propose the extension of a technique that was originally dedicated to glass objects. In contrast to conventional active triangulation techniques that measure the reflection of visible radiation, we measure the thermal emission of a surface, which is locally heated by a laser source. Considering the thermophysical properties of metals, we present a simulation model of heat exchanges that are induced by the process, helping to demonstrate its feasibility on specular metallic surfaces and predicting the settings of the system. With our experimental device, we have validated the theoretical modeling and computed some 3-D point clouds from specular surfaces of various geometries. Furthermore, a comparison of our results with those of a conventional system on specular and diffuse parts will highlight that the accuracy of the measurement no longer depends on the roughness of the surface

Scanning from heating: 3D shape estimation of transparent objects from local surface heating

Today, with quality becoming increasingly important, each product requires three-dimensional in-line quality control. On the other hand, the 3D reconstruction of transparent objects is a very difficult problem in computer vision due to transparency and specularity of the surface. This paper proposes a new method, called Scanning From Heating (SFH), to determine the surface shape of transparent objects using laser surface heating and thermal imaging. Furthermore, the application to transparent glass is discussed and results on different surface shapes are presented

Wood fiber orientation assessment based on punctual laser beam excitation: A preliminary study

International audienceThe EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along the wood fibers. An experiment is presented to show the capacity of such techniques to assess fiber orientation on wood specimen. In addition, an appropriate algorithm is given to extract the orientation of the ellipse

3D measurement of both front and back surfaces of transparent objects by polarization imaging

International audienceWe present a method to recover the 3D shape of both front and back surfaces of smooth transparent objects, such as glass windows or containers. We use a combination of two methods known for the 3D reconstruction of specular surfaces: shape from distortion and shape from polarization. As each transparent surface reflects and transmits incident light, one can see two shifted images by observing the reflection of a pattern on two surfaces nearby. Looking at the reflection of one known point source on the front surface with a calibrated camera, the depth and the orientation of this surface can be determined up to a one dimensional space of solution. This ambiguity is lifted by using the degree of polarization of the reflection, which depends on the incidence angle. Supposing that the front surface is locally at, we show that there is the same ambiguity between position and orientation for the observed reflection coming from the back surface of the object. This ambiguity can again be lifted by using ray-tracing and Mueller calculus. Thus our method enables to measure both the position and the orientation of the two surfaces of a transparent object, with only one polarimetric image. We present an experiment on real objects to evaluate this method