Détermination automatique du seuil de binarisation des modules des gradients par modélisation de leur histogramme

National audienceThis paper presents an enhanced method of image thresholding presented in [6]. The goal is to obtain the edges of objects in an image using a gradient magnitude histogram to automatically determine the threshold value. The method must be simple to be fast and easy to implement on an FPGA circuit. The computed edges will be used within a 3D perception task for high-speed machining security.Nous présentons dans cette communication une amélioration d'une méthode présentée dans [6]. Notre objectif est d'obtenir les contours dans une image à partir de la binarisation des modules des gradients. Ces contours sont obtenus à partir d'un seuil calculé automatiquement sur l'histogramme du module des gradients. La méthode doit être simple pour être rapide, implantable sur un circuit FPGA, et doit exploiter les gradients calculés par ailleurs. La méthode sera intégrée dans une tâche de perception 3D pour la vérification de montage d'usinage en vue de sécuriser l'opération d'usinage grande vitesse

Vérification automatique des montages d'usinage par vision : application à la sécurisation de l'usinage

In High Speed Machining it is of key importance to avoid any collision between the machining tool and the machining setup. If the machining setup has not been assembled correctly by the operator and is not conform to the 3D CAD model sent to the machining unit, such collisions can occur. We have developed a vision system, that utilizes a single camera, to automatically check the conformity of the actual machining setup within the desired 3D CAD model, before launching the machining operation. First, we propose a configuration of the camera within the machining setup to ensure a best acquisition of the scene. In the aim to segmente the image in regions of interest, e.g. regions of the clamping elements and piece, based-on 3D CAD model, we realise a matching between graphes, theorical and real graphe computed from theorical image of 3D-CAD model and real image given by real camera. The graphs are constructed from a simple feature, such as circles and lines, that are manely present in the machining setup. In the aim to define the regions of interest (ROI) in real image within ROI given by 3D CAD model, we project a 3D CAD model in the real image, e.g. augmented reality. To automatically check the accordance between every region defined, we propose to compute three parametres, such as skeleton to represente the form, edges to represent a geometry and Area to represent dimension. We compute a score of accordance between three parameters that will be analyzed in fuzzy system to get a decision of conformity of the clamping element within it definition given in the CAD model. Some cases of machining setup configurations require 3D information to test the trajectory of the machine tool. To get out this situation, we have proposed a new depth from defocus based-method to compute a depth map of the scene. Finally, we present the result of our solution and we show the feasibility and robustness of the proposed solution in differents case of machining setup.Le terme "usinage à porte fermée", fréquemment employé par les PME de l’aéronautique et de l’automobile, désigne l’automatisation sécurisée du processus d’usinage des pièces mécaniques. Dans le cadre de notre travail, nous nous focalisons sur la vérification du montage d’usinage, avant de lancer la phase d’usinage proprement dite. Nous proposons une solution sans contact, basée sur la vision monoculaire (une caméra), permettant de reconnaitre automatiquement les éléments du montage (brut à usiner, pions de positionnement, tiges de fixation,etc.), de vérifier que leur implantation réelle (réalisée par l’opérateur) est conforme au modèle 3D numérique de montage souhaité (modèle CAO), afin de prévenir tout risque de collision avec l’outil d’usinage

Vision-based automatic verification of machining setup : application to machine tools safety

Le terme "usinage à porte fermée", fréquemment employé par les PME de l’aéronautique et de l’automobile, désigne l’automatisation sécurisée du processus d’usinage des pièces mécaniques. Dans le cadre de notre travail, nous nous focalisons sur la vérification du montage d’usinage, avant de lancer la phase d’usinage proprement dite. Nous proposons une solution sans contact, basée sur la vision monoculaire (une caméra), permettant de reconnaitre automatiquement les éléments du montage (brut à usiner, pions de positionnement, tiges de fixation,etc.), de vérifier que leur implantation réelle (réalisée par l’opérateur) est conforme au modèle 3D numérique de montage souhaité (modèle CAO), afin de prévenir tout risque de collision avec l’outil d’usinage.In High Speed Machining it is of key importance to avoid any collision between the machining tool and the machining setup. If the machining setup has not been assembled correctly by the operator and is not conform to the 3D CAD model sent to the machining unit, such collisions can occur. We have developed a vision system, that utilizes a single camera, to automatically check the conformity of the actual machining setup within the desired 3D CAD model, before launching the machining operation. First, we propose a configuration of the camera within the machining setup to ensure a best acquisition of the scene. In the aim to segmente the image in regions of interest, e.g. regions of the clamping elements and piece, based-on 3D CAD model, we realise a matching between graphes, theorical and real graphe computed from theorical image of 3D-CAD model and real image given by real camera. The graphs are constructed from a simple feature, such as circles and lines, that are manely present in the machining setup. In the aim to define the regions of interest (ROI) in real image within ROI given by 3D CAD model, we project a 3D CAD model in the real image, e.g. augmented reality. To automatically check the accordance between every region defined, we propose to compute three parametres, such as skeleton to represente the form, edges to represent a geometry and Area to represent dimension. We compute a score of accordance between three parameters that will be analyzed in fuzzy system to get a decision of conformity of the clamping element within it definition given in the CAD model. Some cases of machining setup configurations require 3D information to test the trajectory of the machine tool. To get out this situation, we have proposed a new depth from defocus based-method to compute a depth map of the scene. Finally, we present the result of our solution and we show the feasibility and robustness of the proposed solution in differents case of machining setup

Contrôle automatique des montages d'usinage par vision monoculaire

National audienc

Automatic verification of machining setups using computer vision

International audienc

A new chain-processing-based computer vision system for automatic checking of machining set-up - Application for machine tools safety

International audienceIn high-speed machining it is of key importance to avoid any collision between the machine tool and the machining setup. If the machining setup has not been assembled correctly by the operator and does not conform to the 3D CAD model sent to the machining unit, such collisions may occur. This paper presents a new chain-processing-based computer vision system to automatically avoid collision between tool and machining setup components by checking that the actual machining setup is in conformity with the desired 3D CAD model used to generate the tool trajectory. This computer vision system utilizes a single camera to automatically check conformity before the start of the machining operation. The proposed solution was tested in different kinds of machining setups , and each step of the proposed chain was evaluated. The results show the robustness of the solution for different kinds of machining setups

Computer-vision-based automatic verification of machining setups: method for automatic pose estimation

International audienc

Contrôle automatique des montages d'usinage par vision monoculaire

National audienc

Vérification automatique des montages d'usinage par vision (application à la sécurisation de l'usinage)

Le terme "usinage à porte fermée", fréquemment employé par les PME de l aéronautique et de l automobile, désigne l automatisation sécurisée du processus d usinage des pièces mécaniques. Dans le cadre de notre travail, nous nous focalisons sur la vérification du montage d usinage, avant de lancer la phase d usinage proprement dite. Nous proposons une solution sans contact, basée sur la vision monoculaire (une caméra), permettant de reconnaitre automatiquement les éléments du montage (brut à usiner, pions de positionnement, tiges de fixation,etc.), de vérifier que leur implantation réelle (réalisée par l opérateur) est conforme au modèle 3D numérique de montage souhaité (modèle CAO), afin de prévenir tout risque de collision avec l outil d usinage.In High Speed Machining it is of key importance to avoid any collision between the machining tool and the machining setup. If the machining setup has not been assembled correctly by the operator and is not conform to the 3D CAD model sent to the machining unit, such collisions can occur. We have developed a vision system, that utilizes a single camera, to automatically check the conformity of the actual machining setup within the desired 3D CAD model, before launching the machining operation. First, we propose a configuration of the camera within the machining setup to ensure a best acquisition of the scene. In the aim to segmente the image in regions of interest, e.g. regions of the clamping elements and piece, based-on 3D CAD model, we realise a matching between graphes, theorical and real graphe computed from theorical image of 3D-CAD model and real image given by real camera. The graphs are constructed from a simple feature, such as circles and lines, that are manely present in the machining setup. In the aim to define the regions of interest (ROI) in real image within ROI given by 3D CAD model, we project a 3D CAD model in the real image, e.g. augmented reality. To automatically check the accordance between every region defined, we propose to compute three parametres, such as skeleton to represente the form, edges to represent a geometry and Area to represent dimension. We compute a score of accordance between three parameters that will be analyzed in fuzzy system to get a decision of conformity of the clamping element within it definition given in the CAD model. Some cases of machining setup configurations require 3D information to test the trajectory of the machine tool. To get out this situation, we have proposed a new depth from defocus based-method to compute a depth map of the scene. Finally, we present the result of our solution and we show the feasibility and robustness of the proposed solution in differents case of machining setup.TOULOUSE2-SCD-Bib. electronique (315559903) / SudocSudocFranceF