KEYWORDS: Sensors, Pose estimation, Visualization, RGB color model, Information visualization, Education and training, Point clouds, Data modeling, Machine learning, Image segmentation
After more than three decades of research in robot manipulation problems, we observed a considerable level of maturity in different related problems. Many high-performant objects pose tracking exists, one of the main problems for these methods is the robustness again occlusion during in-hand manipulation. This work presents a new multimodal perception approach in order to estimate the pose of an object during an in-hand manipulation. Here, we propose a novel learning-based approach to recover the pose of an object in hand by using a regression method. Particularly, we fuse the visual-based tactile information and depth visual information in order to overpass occlusion problems commonly presented during robot manipulation tasks. Our method is trained and evaluated using simulation. We compare the proposed method against different state-of-the-art approaches to show its robustness in hard scenarios. The recovered results show a reliable increment in performance, while they are obtained using a benchmark in order to obtain replicable and comparable results.
Conventional methods used to inspect the molten pool surface induced by arc welding processes are based on post-welding evaluation using destructive or semi-destructive testing methods. Many attempts were performed to develop alternative and nondestructive tests. In this context, a polarimetric vision methodology is evaluated. The polarimetric parameters are measured from the thermal radiations emitted by the hot liquid metal at a wavelength within an arc plasma blind spectral window. The Stokes parameters and their segmentation within a Gaussian mixture model allow to discriminate artifacts at the surface of the liquid metal. After weld pool solidification, the use of scanning electron microscopy and energy dispersive spectroscopy allow to identify the artifacts, i.e., floating alumina particles.
This paper presents a passive polarimetry method using a division of aperture optical device in order to segment the weld pool surface of the welding. Due to the high specularity of the surface of the weld pool, we use polarimetric data in order to facilitate it’s segmentation in the liquid state. In this paper, we propose to combine two segmentation methods: Watershed Transform and the Level Set to ensure a better result. Our ultimate goal of this study is to provide real-time quality control of the surface of molten metal during the welding process while utilizing the additional information provided by the polarimetric data.
KEYWORDS: Polarization, Polarimetry, Stereoscopy, 3D image processing, Far infrared, Near infrared, Metals, 3D metrology, Dielectric polarization, Cameras, Glasses, 3D modeling, Infrared radiation, Polarizers
This paper describes the use of polarization information to estimate the shape of emissive objects in the field of nonconventional imaging techniques for 3D digitization. Using “Shape from Polarization” method which is applied in the far infrared for transparent object and in the near infrared for the molten metal. Our study shows that by studying the state of polarization of the emitted radiation from the object, normal of the surface can be determined and subsequently the 3D shape.
In the domain of 3D measurement for inspection purposes, standard systems based on triangulation approaches, can be limited by the nature of the observed surface. When the surface is not lambertian, i.e. highly reflective or transparent, other strategies to ease the measurement need to be developed. The idea of using the polarization property of the light is one of them. This was explored to be a complementary modality, in triangulation or shape from distortion methods, or used in a standalone system through the concept of "shape from polarization". In this paper we propose a short state of the art of the usage of polarimetric imaging for the study of surface and the measurement of 3D data. We focus on recent development applied to the industrial domain, or the health domain.
Today, industries ensure the quality of their manufactured products through computer vision techniques and nonconventional imaging. Three-dimensional (3-D) scanners and nondestructive testing (NDT) systems are commonly used independently for such applications. Furthermore, these approaches combined constitute hybrid systems, providing a 3-D reconstruction and NDT analysis. These systems, however, suffer from drawbacks such as errors during the data fusion and higher cost for manufacturers. In an attempt to solve these problems, a single active thermography system based on scanning-from-heating is proposed in this paper. In addition to 3-D digitization of the object, our contributions are twofold: (1) the nonthrough defect detection for a homogeneous metallic object and (2) fiber orientation assessment for a long fiber composite material. The experiments on steel and aluminum plates show that our method achieves the detection of nonthrough defects. Additionally, the estimation of the fiber orientation is evaluated on carbon-fiber composite material.
The search for an efficient on-line monitoring system focused on the real-time analysis of arc welding quality is an active area of research. The topography and the superficial temperature field of the weld pool can provide important information which can be used to regulate the welding parameters for depositing consistent welds. One difficulty relies on accessing this information despite the bright dazzling welding arc. In the present work, Stokes polarimetry and associated shape-from-polarization methods are applied for the analysis of the weld pool through its 810 nm-wavelength infrared emissions. The obtained information can provide a better understanding of the process, such as the usage of the topography to seek Marangoni flows direction, or to have a denser 3D map to improve numerical simulation models.
A nondestructive inspection method using an infrared detection system is presented in this paper; the system uses a YAG laser as excitation point. The material thermal response to this excitation is processed for the detection of volume defects, this technique integrated into a 3D scanning system allows us to get a 3D scan of the object as well as defects detection.
We 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.
Fashion and design greatly influence the conception of manufactured products which now exhibit complex forms and shapes. Two-dimensional quality control procedures (e.g., shape, textures, colors, and 2D geometry) are progressively being replaced by 3D inspection methods (e.g., 3D geometry, colors, and texture on the 3D shape) therefore requiring a digitization of the object surface. Three dimensional surface acquisition is a topic which has been studied to a large extent, and a significant number of techniques for acquiring 3D shapes has been proposed, leading to a wide range of commercial solutions available on the market. These systems cover a wide range from micro-scale objects such as shape from focus and shape from defocus techniques, to several meter sized objects (time of flight technique). Nevertheless, the use of such systems still encounters difficulties when dealing with non-diffuse (non Lambertian) surfaces as is the case for transparent, semi-transparent, or highly reflective materials (e.g., glass, crystals, plastics, and shiny metals). We review and compare various systems and approaches which were recently developed for 3D digitization of transparent objects.
A novel reconstruction scheme using ultraviolet (UV) structured point for transparent objects three-dimensional (3D) measurement was reported in our previous works. We address two main approaches behind a low-cost system within two suggested configurations (according to the structured light generation source: UV spot and UV line) in order to improve the results accuracy, which endows our system with its adaptability for industrial applications. The first approach consists of determining the optimal configuration of the practical setup while controlling the modeling error (related to the 3D reconstruction approach) with the implementation of an additional validation method in the reconstruction process. The second approach deals with a method which tracks the fluorescence points in the presence of noises inherent to our acquisition system. The specificity of the implemented tracking method relies on spectroscopic analysis. Indeed, experimental investigation has been also carried out to characterize the application. Some digitized objects are presented with an accuracy never reached by any previously reported works dealing with the digitization of transparent objects without any prior preparation.
Automatic industrial surface inspection methodology based on Magnetic Particle Inspection is developed from image
acquisition to defect classification. First the acquisition system is optimized, then tubular material images are acquired,
reconstructed then stored. The characteristics of the crack-like defects with respect to its geometric model and curvature
are used as a priori knowledge for mathematical morphology and linear filtering. After the segmentation and binarization
of the image, vast amount of defect candidates exist. Finally classification is performed with decision tree learning
algorithm due to its robustness and speed. The parameters for mathematical morphology, linear filtering and
classification are analyzed and optimized with Design Of Experiments based on Taguchi approach. The most significant
parameters obtained may be analyzed and tuned further. Experiments are performed on tubular materials and evaluated
by its accuracy and robustness by comparing ground truth and processed images. The result is promising with 97 % True
Positive and only 0.01 % False Positive rate on the testing set.
Classical 3D inspection systems require users to coat transparent objects before measurement. Experimental techniques
via non contact measurement, suggested in literature, do not treat inter reflections. The aim of our work is to develop a
non contact 3D measurement system for transparent objects by using a polarimetric imaging method in far infrared
range. The classical approach relies on the use of orthographic model generated by a telecentric lens in practical setup.
However telecentric lenses working in far infrared range are not available. Therefore, we have to adapt pinhole model
corresponding to non-telecentric lenses for shape from polarization. In this paper we introduce a 3D reconstruction
method to exploit polarimetric imaging with perspective model.
We also propose two mathematical approaches in order to reduce reconstruction error: data analysis method to better
estimate Stokes parameters and a validation method after Stokes parameters estimation. These techniques are applicable
irrespective of the nature of the selected model and any linear system resolution.
This paper deals with a 3D measurement system based on the "Shape from Polarization" method applied for transparent
objects.
The method is an application of polarization imaging techniques and its principle is as follows: after being reflected, an
unpolarized light becomes partially linearly polarized. By analyzing its polarization parameters and by knowing the
refractive index of the object to be controlled, the surface normals can be evaluated. Finally, the 3D shape is obtained by
integrating the normals field.
Section 1 introduces the opportunity to use polarisation imaging, section 2 recalls the measurement method and describes
the angle measurement ambiguities naturally appearing and discusses how to overcome them, section 3 introduces the
measurement setup and a part of its calibration and section 4 describes some examples on transparent objects.
This paper aims at reviewing the recent published works dealing with industrial applications which rely on polarization imaging.
A general introduction presents the basics of polarimetry and then 2D and 3D machine vision application are presented as well as the latest evolution in term of high speed polarimetric imaging.
In order to achieve better quality on their products, manufacturers
now use more and more artificial vision systems during their process.
Concerning transparent objects the task is not trivial and requires controlling the whole lighting of the scene. This paper deals with a polarization imaging method and its application to shape measurement of transparent objects. Our aim is to develop a low cost system based on a unique viewpoint and using industrial components. We show how to overcome ambiguities appearing during the measurement process.
We propose a new application of « Shape from Polarization » method to reconstruct surface shapes of specular metallic objects. Studying the polarization state of the reflected light is very useful to get information on the surface normals. After reflection, an unpolarized light wave becomes partially linearly polarized. Such a wave, can be described by its three parameters: intensity, degree of polarization, and angle of polarization. By using the refractive index of the surface, a relationship between the degree of polarization and the reflection angle can be established. Unfortunately, the relation commonly used for dielectrics, cannot be applied since the refractive index of metallic surfaces is complex. To get a similar relation, we apply a usual approximation valid in the visible region. The Fresnel reflectance model can also provide a relationship between the angle of polarization and the incidence plane orientation. Thus, the reflection angle and the incidence plane orientation give the surface normals. The shape is finally computed by integrating the normals with a relaxation algorithm.
Applications on metallic objects made by stamping and polishing are also described, and show the efficiency of our system to discriminate shape defects. Future works will consist in integrating the system into an automatic process of defects detection.
In the field of industrial vision, extracting the 3D shape information of highly reflective metallic objects is still a delicate task. This paper presents a new application of "Shape from Polarization" method to specular metallic surfaces. Studying the state of polarization of the reflected light is very useful to get information on the normals of the surface. This article demonstrates how to extend the commonly used method for dielectric to metallic surfaces. Applications on shape defects detection are also discussed, and the efficiency of the system to discriminate defects on metallic objects made by stamping and polishing is presented.
KEYWORDS: 3D scanning, Biological research, 3D image processing, Scanners, Image analysis, 3D modeling, 3D acquisition, Image filtering, Wavelets, Image acquisition
We propose in this paper an application of multiresolution analysis techniques to extract information contained in the growth increments of a bivalve mollusk called: Calyptogena. The first stage consists in extracting a range image of the mollusk’s shell using a 3-D scanner. Applying a multiresolution analysis enables us to localize precisely those growth increments by preserving relevant details. Moreover, interesting spatial and frequency properties of the multiresolution analysis underline information contained on the shell. Intra-individual variation and inter-individual variations are compared to assume some conclusions as for the ontogenetic evolution of the animal such as periodicities, which can be later related to certain regular changes in its environment.
Many implementations of computer generated holograms (CGH’s) or diffractive optical elements (DOE’s) onto spatial light modulators (SLM’s) have already been considered. In this paper, we first review the various types of SLM’s available for DOE’s and the implementations of DOE’s onto SLM’s already reported in the literature. Then we investigate the point in displaying DOE’s onto SLM’s that couple phase and amplitude modulations, such as twisted nematic-liquid crystal displays (TN-LCD's): we provide computer simulations as well as experimental results.
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