Fringe-pattern projection (FPP) techniques are commonly used for surface-shape measurement in a wide range of applications including object and scene modeling, part inspection, and reverse engineering. Periodic intensity fringe patterns with a specific amplitude are projected by the projector onto an object and a camera captures images of the fringe patterns, which appear distorted by the object surface from the perspective of the camera. The images are then used to compute the height or depth of the object at each pixel. One of the problems with FPP is that camera sensor saturation may occur if there is a large change in ambient lighting or a large range in surface reflectivity when measuring object surfaces. Camera sensor saturation occurs when the reflected intensity exceeds the maximum quantization level of the camera. A low SNR occurs when there is a low intensity modulation of the fringe pattern compared to the amount of noise in the image. Camera sensor saturation and low SNR can result in significant measurement error. Careful selection of the camera aperture or exposure time can reduce the error due to camera sensor saturation or low SNR. However, this is difficult to perform automatically, which may be necessary when measuring objects in uncontrolled environments where the lighting may change and objects have different surface reflectivity. This research presents three methods to avoid camera sensor saturation when measuring surfaces subject to changes in ambient lighting and objects with a large range in reflectivity. All these methods use the same novel approach of lowering the maximum input gray level (MIGL) to the projector for saturation avoidance. This approach avoids saturation by lowering the reflected intensity so that formerly saturated intensities can be captured by the camera. The first method of saturation avoidance seeks a trade-off between robustness to intensity saturation and low SNR. Measurements of a flat white plate at different MIGL resulted in a trade-off MIGL that yielded the highest accuracy for a single adjustment of MIGL that is uniform within and across the projected images. The second method used several sets of images, taken at constant steps of MIGL, and combined the images pixel-by-pixel into a single set of composite images, by selecting the highest unsaturated intensities at each pixel. White plate measurements using this method had comparable accuracy to the first method but required more images to form the composite image. Measurement of a checkerboard showed a higher accuracy than the first method since the second method maintains a higher SNR when the object has a large range of reflectivity. The last method also used composite images where the step size was determined dynamically, based on the estimated percentage of pixels that would become unsaturated at the next step. In measurements of a flat white plate and a checkerboard the dynamic step size was found to add flexibility to the measurement system compared to the constant steps using the second method. Using dynamic steps, the measurement system was able to measure objects with either a low or high range of reflectivity with high accuracy and without manually adjusting the step size. This permits fully automated measurement of unknown objects with variable reflectivity in unstructured environments with changing lighting conditions. The methods can be used for measurement in uncontrolled environments, for specular surfaces, and those with a large range of reflectivity or luminance. This would allow a wider range of measurement applications using FPP techniques.

The utilisation of 3D digitisation and visualisation has grown considerably since 2008 and is becoming an increasingly useful tool for the digital documentation and metric analysis of archaeological artefacts and skeletal remains. It provides public access to rare and fragile specimens of palaeontological and palaeopathological importance whilst reducing the physical impact on these remains. Research in engineering and computer vision provides some insight into the impact of surface properties such as colour, specularity, reflectance and shape on the quality of the recorded 3D image, but within the archaeological and palaeontological disciplines comparable work has not yet been developed. If archaeology and anthropology are to provide long term reliable data from archaeological and palaeontological specimens in a way that doesn’t require repeated re-digitisation, we need to understand the impacts that the taphonomic histories of such samples have on our ability to 3D record them. Understanding the relationship of these taphonomic histories and the surface and optical properties will promote informed choices about the suitability of recording techniques. This thesis considers the taphonomic processes that affect the preservation of bone over archaeological, forensic and palaeontological timescales and the effect this has on the quality of 3D digital models. The digital refit of fragmentary bone samples is considered in relation to the effect of taphonomic alterations to bone. Conclusions regarding the key taphonomic factors and 3D digital model quality are drawn and areas of further work are identified.

La fabrication de pièces manufacturées génère un nombre très important de données de différents types définissant les géométries de fabrication ainsi que la qualité de production. Ce travail de thèse s’inscrit dans le cadre de la réalisation d’un système de vision cognitif dédié à l’évaluation d’objets 3D manufacturés incluant éventuellement des surfaces gauches, en tenant compte des tolérances géométriques et des incertitudes. Ce système permet un contrôle exhaustif de pièces manufacturées et offre la possibilité d’une inspection tridimensionnelle automatique de la pièce. La mise en place d’un système de mesures multi-capteurs (passifs et actifs) a permis d’améliorer significativement la qualité d’évaluation par le biais d’une reconstruction tridimensionnelle enrichie de l’objet à évaluer. En particulier, nous avons employé simultanément un système stéréoscopique de vision et un système à projection de lumière structurée afin de reconstruire les contours et les surfaces de différents objets 3D. / Producing industrially manufactured parts generates a very large number of data of various types defining the manufacturing geometries as well as the quality of production. This PhD work has been carried out within the framework of the realization of a cognitive vision system dedicated to the 3D evaluation of manufactured objects including possibly free form surfaces, taking into account the geometric tolerances and uncertainties. This system allows the comprehensive control of manufactured parts, and provides the means for their automated 3D dimensional inspection. The implementation of a multi-sensor (passive and active) measuring system enabled to improve significantly the assessment quality through an enriched three-dimensional reconstruction of the object to be evaluated. Specifically, we made use simultaneously of a stereoscopic vision system and of a structured light based system in order to reconstruct the edges and surfaces of various 3D objects.

This diploma thesis deals with the design of a 3D optical scanner using the structured light projection method. The aim of this thesis is to demonstrate the principles and processes of 3D scanning by using the DLP LightCrafter projector and the ImagingSource camera. The individual stages of the measurement process will be implemented to the Matlab software environment to describe the various principles and methods which can be used for digitizing the objects.

The general aim of my master´s thesis is to study the actual principles of 3D scanning, the anatomy of human teeth, use of 3D scanning in dentistry and other medical fields. Another part of this thesis is about software and hardware design of 3D scanning system, which enable us to scan dental casts. This design is using webcam, projector and turntable. The principle of scanning is based on the activ triangulation. The output of 3D scanner is a horde of spots, which are used for reconstruction of a surface. The reconstructed surface is finally saved as .stl format.

The utilisation of 3D digitisation and visualisation has grown considerably since 2008 and is becoming an increasingly useful tool for the digital documentation and metric analysis of archaeological artefacts and skeletal remains. It provides public access to rare and fragile specimens of palaeontological and palaeopathological importance whilst reducing the physical impact on these remains. Research in engineering and computer vision provides some insight into the impact of surface properties such as colour, specularity, reflectance and shape on the quality of the recorded 3D image, but within the archaeological and palaeontological disciplines comparable work has not yet been developed. If archaeology and anthropology are to provide long term reliable data from archaeological and palaeontological specimens in a way that doesn’t require repeated re-digitisation, we need to understand the impacts that the taphonomic histories of such samples have on our ability to 3D record them. Understanding the relationship of these taphonomic histories and the surface and optical properties will promote informed choices about the suitability of recording techniques. This thesis considers the taphonomic processes that affect the preservation of bone over archaeological, forensic and palaeontological timescales and the effect this has on the quality of 3D digital models. The digital refit of fragmentary bone samples is considered in relation to the effect of taphonomic alterations to bone. Conclusions regarding the key taphonomic factors and 3D digital model quality are drawn and areas of further work are identified. / Arts and Humanities Research Council

[pt] As pinças ópticas tornaram-se uma ferramenta importante na pesquisa multidisciplinar, permitindo a manipulação e estudo de partículas em micro e nanoescala. Aqui, descrevemos o desenvolvimento de dois experimentos de pinça óptica no cerne da optomecânica levitada: uma pinça óptica a vácuo Gaussiana e uma pinça óptica a vácuo com luz estruturada. No experimento Gaussiano, descrevemos em detalhes sua construção e seu uso para testar características de movimento estocástico sujeito a forças efetivas não-lineares geradas através de feedback elétrico. Em seguida, passamos para a configuração de luz estruturada. Utilizando um Modulador Espacial de Luz, desenvolvemos uma pinça óptica a vácuo com a capacidade de gerar potenciais ópticos arbitrários, incluindo não-linearidades e armadilhas para múltiplas partículas. Os experimentos desenvolvidos neste trabalho abrem caminho para novos métodos de controle de movimento de partículas, forças e interações, expandindo ainda mais a caixa de ferramentas da optomecânica levitada. / [en] Optical tweezers have become an important tool in multidisciplinary research, allowing for the manipulation and study of micro- and nano-scale particles. Here, we describe the development of two optical tweezer experiments at the heart of levitated optomechanics: a Gaussian and a structured light vacuum optical tweezer. In the Gaussian experiment, we describe in detail its construction and its use to test features of stochastic motion subject to nonlinear effective forces generated via electric feedback. Next, we move to the structured light setup. Using a Spatial Light Modulator, we develop a vacuum optical tweezer with the capability of engineering arbitrary optical landscapes, including non-linearities and multi-particle traps. The experiments developed in this work pave the way to novel methods for controlling particle motion, forces and interactions, further extending the levitated optomechanics toolbox.

<p dir="ltr">Monitoring of additive manufacturing (AM) processes allows for saving time and materials by detecting and addressing errors as they occur. When fast and efficient, the monitored AM of each unit can be completed in less time, thus improving overall economics and allowing the user to accept a higher capacity of AM requests with the same number of machines. Based on existing AM process monitoring solutions, it is very challenging for any approach to analyze full-resolution sensor data that yields three-dimensional (3D) topological information for closed-loop real-time applications. It is also challenging for any approach to be simultaneously capable of <i>plug-and-play</i> operation once AM hardware and sensor subsystems are configured. This thesis presents a novel method to speed up error detection in an additive manufacturing (AM) process by minimizing the necessary three-dimensional (3D) reconstruction and comparison. A structured light 3D imaging technique is developed that has native pixel-by-pixel mapping between the captured two-dimensional (2D) absolute phase image and the reconstructed 3D point cloud. This 3D imaging technique allows error detection to be performed in the 2D absolute phase image domain prior to 3D point cloud generation, which drastically reduces complexity and computational time. For each layer of an AM process, an artificial threshold phase image is generated and compared to the measured absolute phase image to identify error regions. Compared to an existing AM error detection method based on 3D reconstruction and point cloud processing, experimental results from a material extrusion (MEX) AM process demonstrate that the proposed method has comparable error detection capabilities. The proposed method also significantly increases the error detection speed, where the relationship between the speed improvement factor and the percentage of erroneous pixels in the captured 2D image follows a power-law relationship. The proposed method was also successfully used to implement closed-loop error correction to demonstrate a potential process monitoring application.</p>

<p dir="ltr">Over the last few decades, three-dimensional (3D) optical imaging and sensing techniques have attracted much attention from both academia and industries. Owing to its capability of gathering more information than conventional 2D imaging, it has been successfully adopted in many applications on the macro scale which ranges from sub-meters to meters such as entertainment, commercial electronics, manufacturing, and construction. For example, the iPhone “FaceID” sensor is used for facial recognition, and the Microsoft Kinect is used to track body motion in video games. With recent advances in many technical fields, such as semiconductor packaging, additive manufacturing, and micro-robots, there is an increasing need for microscopic 3D imaging, and several techniques including interferometry, confocal microscopy, focus variation, and structured light have been developed and adopted in these industries. Among these techniques, the structured light 3D imaging technique is considered one of the most promising techniques for in-situ metrology, owing to its advantage of simple configuration and high measurement speed. However, several challenges must be addressed in employing the structured-light 3D imaging technique in these fields.</p><p dir="ltr">The first challenge is the limited measurement range caused by the limited depth of field (DOF). Given the necessity for large magnification in the microscopic structured light system, the DOF becomes notably shallow, especially when pin-hole lenses are adopted. This issue is exacerbated by the fact that the measured objects in the aforementioned industries could contain miniaturized features spanning a broad height range. To address this problem, we introduce the idea of the focus stacking technique, wherein the focused pixels gathered from various focus settings are merged to form an all-in-focus image, into the structured-light 3D imaging. We further developed a computational framework that utilizes the phase information and fringe contrast of the projected fringe patterns to mitigate the influence of object textures.</p><p dir="ltr">The second challenge is the 3D imaging speed. The 3D measurement speed is a crucial factor for in-situ applications. We improved the large DOF 3D imaging speed by reducing the required fringe images from two aspects: 1) We developed a calibration method for multifocus pin-hole mode, which can eliminate the necessity of the 2D image alignment. The conventional method based on circle patterns will be affected during the feature extraction process by the significant camera defocusing. In contrast, our proposed method is more robust since it uses virtual features extracted from a reconstructed white flat surface under a pre-calibrated focus setting. 2)We developed a phase unwrapping method with the assistance of the electrically tunable lens (ETL), which is an optical component we used to capture fringe images under various focus settings. The proposed phase unwrapping method leverages the focal plane position of each focus setting to estimate a rough depth map for the geometric-constraint phase unwrapping algorithm. By doing this, the method eliminates the limitation on the effective working depth range and becomes feasible in large DOF 3D imaging.</p><h4>Even with all previous methodologies, the efficiency of large DOF 3D imaging is still not high enough under certain circumstances. One of the major reasons is that we can still only use a series of pre-defined focus settings to run the focus stacking, since we have no prior on the measured objects. This issue could lead to low measurement efficiency when the depth range of the measured objects does not cover the whole enlarged DOF. To improve the performance of the system under such situations, we developed a method that introduces another computational imaging technique: the focal sweep technique, to help determine the optimal focus settings adapting to different measured objects.</h4><h4>In summary, this dissertation contributed to high-speed, large depth-of-field, and automated 3D imaging, which can be used in micro-scale applications from the following aspects: (1) enlarging the DOF of the microscopic 3D imaging using the focus stacking technique; (2) developing methods to improve the speed of large DOF microscopic 3D imaging; and (3) developing a method to improve the efficiency of the focus stacking under certain circumstances. These contributions can potentially enable the structured-light 3D imaging technique to be an alternative 3D microscopy approach for many academic studies and industry applications.</h4><p></p>

In this thesis, we investigate the formulation, optimization and ambiguities in single-image 3D surface reconstruction from geometric and photometric constraints. We examine linear, discrete and quadratic constraints for shape from planar curves, shape from texture, and shape from shading. The problem of recovering 3D shape from the projection of planar curves on a surface is strongly motivated by perception studies. Applications include single-view modeling and uncalibrated structured light. When the curves intersect, the problem leads to a linear system for which a direct least-squares method is sensitive to noise. We derive a more stable solution and show examples where the same method produces plausible surfaces from the projection of parallel (non-intersecting) planar cross sections. The problem of reconstructing a smooth surface under constraints that have discrete ambiguities arise in areas such as shape from texture, shape from shading, photometric stereo and shape from defocus. While the problem is computationally hard, heuristics based on semidefinite programming may reveal the shape of the surface. Finally, we examine the shape from shading problem without boundary conditions as a polynomial system. This formulation allows, in generic cases, a complete solution for ideal polyhedral objects. For the general case we propose a semidefinite programming relaxation procedure, and an exact line search iterative procedure with a new smoothness term that favors folds at edges. We use this numerical technique to inspect shading ambiguities.