In-process surface profile assessment of rotary machined timber using a dynamic photometric stereo technique

Machining operations have advanced in speed and there is an increasing demand for higher quality surface finish. It is therefore necessary to develop real-time surface inspection techniques which will provide sensory information for controlling the machining processes. This paper describes a practical method for real-time analysis of planed wood using the photometric stereo technique. Earlier research has shown that the technique is very effective in assessing surface waviness on static wood samples. In this paper, the photometric stereo method is extended to real industrial applications where samples are subjected to rapid movements. Surface profiles extracted from the dynamic photometric stereo method are compared with those from the static measurements and the results show that there is a high correlation between the two methods

Artificial intelligence for advanced manufacturing quality

100 p.This Thesis addresses the challenge of AI-based image quality control systems applied to manufacturing industry, aiming to improve this field through the use of advanced techniques for data acquisition and processing, in order to obtain robust, reliable and optimal systems. This Thesis presents contributions onthe use of complex data acquisition techniques, the application and design of specialised neural networks for the defect detection, and the integration and validation of these systems in production processes. It has been developed in the context of several applied research projects that provided a practical feedback of the usefulness of the proposed computational advances as well as real life data for experimental validation

3D freeform surface measurement on coordinate measuring machine using photometric stereo method

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonSurface metrology has been widely used in manufacturing for many years. There has been a wide range of techniques applied for measuring surface topography. A photometric stereo technique is one of the best ways for the analysis of three-dimensional (3D) surface textural patterns. Many published works are concerned the developed approach for recovering the 3D profiles from surface normal. This research not only presents a methodology used to retrieve the profiles of surface roughness standards but also investigates the uncertainty estimation of textural measurement determined by the photometric stereo method. Various input quantities have been studied such as pixel error from recovered 3D surface textural patterns, the power of light source which involved with surface roughness average (Ra) value and the effect of room temperature. The surface roughness standards were utilized as the reference value. In term of increasing accuracy of the reference value, a contact method (stylus instrument) was used to calibrate them. Illumination angles of light source had some influence on the measurement results. A coordinate measuring machine (CMM) was used for holding the light source in order to study the effects of tilt and slant angles. The effect of tilt and slant angles were investigated. The results of these experiments successfully indicated that the angle used in photometric stereo method played an important role to the accuracy level of the roughness measurement results. The surface roughness specimen manufactured by a Computer Numerical Control (CNC) was applied to validate the capability of the photometric stereo system.The royal Thai government, ministry of sciences and technology and national institute of metrology Thailand (NIMT

Forum Bildverarbeitung 2016

Bildverarbeitung spielt in vielen Bereichen der Technik zur schnellen und berührungslosen Datenerfassung eine Schlüsselrolle. Der vorliegende Tagungsband des „Forums Bildverarbeitung“, das am 1. und 2. Dezember 2016 in Karlsruhe als Veranstaltung des Karlsruher Instituts für Technologie und des Fraunhofer-Instituts für Optronik, Systemtechnik und Bildauswertung stattfand, enthält die Aufsätze der eingegangenen Beiträge. Darin wird über aktuelle Trends und Lösungen der Bildverarbeitung berichtet

Semantic models of scenes and objects for service and industrial robotics

What may seem straightforward for the human perception system is still challenging for robots. Automatically segmenting the elements with highest relevance or salience, i.e. the semantics, is non-trivial given the high level of variability in the world and the limits of vision sensors. This stands up when multiple ambiguous sources of information are available, which is the case when dealing with moving robots. This thesis leverages on the availability of contextual cues and multiple points of view to make the segmentation task easier. Four robotic applications will be presented, two designed for service robotics and two for an industrial context. Semantic models of indoor environments will be built enriching geometric reconstructions with semantic information about objects, structural elements and humans. Our approach leverages on the importance of context, the availability of multiple source of information, as well as multiple view points showing with extensive experiments on several datasets that these are all crucial elements to boost state-of-the-art performances. Furthermore, moving to applications with robots analyzing object surfaces instead of their surroundings, semantic models of Carbon Fiber Reinforced Polymers will be built augmenting geometric models with accurate measurements of superficial fiber orientations, and inner defects invisible to the human-eye. We succeeded in reaching an industrial grade accuracy making these models useful for autonomous quality inspection and process optimization. In all applications, special attention will be paid towards fast methods suitable for real robots like the two prototypes presented in this thesis

Realistic visualisation of cultural heritage objects

This research investigation used digital photography in a hemispherical dome, enabling a set of 64 photographic images of an object to be captured in perfect pixel register, with each image illuminated from a different direction. This representation turns out to be much richer than a single 2D image, because it contains information at each point about both the 3D shape of the surface (gradient and local curvature) and the directionality of reflectance (gloss and specularity). Thereby it enables not only interactive visualisation through viewer software, giving the illusion of 3D, but also the reconstruction of an actual 3D surface and highly realistic rendering of a wide range of materials. The following seven outcomes of the research are claimed as novel and therefore as representing contributions to knowledge in the field: A method for determining the geometry of an illumination dome; An adaptive method for finding surface normals by bounded regression; Generating 3D surfaces from photometric stereo; Relationship between surface normals and specular angles; Modelling surface specularity by a modified Lorentzian function; Determining the optimal wavelengths of colour laser scanners; Characterising colour devices by synthetic reflectance spectra

3D inspection of wafer bump quality without explicit 3D reconstruction.

Zhao Yang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 87-95).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Objectives of the Thesis --- p.1Chapter 1.2 --- Wafer bumping inspection by using Biplanar Disparity approach --- p.2Chapter 1.3 --- Thesis Outline --- p.4Chapter 2 --- Background --- p.5Chapter 2.1 --- What is wafer bump? --- p.5Chapter 2.1.1 --- Common defects of wafer bump --- p.6Chapter 2.1.2 --- Literature review on exist wafer bump inspection method --- p.11Chapter 3 --- Model 1: the one camera model-Homography approach --- p.21Chapter 3.1 --- The introduction of the theoretical base of model 1 --- p.21Chapter 3.1.1 --- The objective of model 1 --- p.21Chapter 3.1.2 --- Desires --- p.22Chapter 3.1.3 --- Some background knowledge on Homography --- p.22Chapter 3.2 --- "Model 1- ""Pseudo Homography"" Approach" --- p.24Chapter 3.2.1 --- The description of the configuration of model 1 --- p.24Chapter 3.2.2 --- The condition of pseudo Homography --- p.25Chapter 3.2.3 --- The formation of pseudo Homgraphy H --- p.26Chapter 3.3 --- Methodology of treatment of the answer set --- p.32Chapter 3.3.1 --- Singular Value Decomposition-SVD --- p.32Chapter 3.3.2 --- The Robust Estimation --- p.33Chapter 3.3.3 --- Some experimental results by using manmade Ping Pang balls to test SVD[31] and Robust Estimation [24] --- p.35Chapter 3.3.4 --- the measurement of the Homography matrix answer set --- p.37Chapter 3.4 --- Preliminary experiment about model 1 --- p.43Chapter 3.5 --- Problems unsolved --- p.47Chapter 4 --- Model 2: the two camera model-Biplanar Disparity approach --- p.48Chapter 4.1 --- Theoretical Background --- p.48Chapter 4.1.1 --- the linearization of Homography matrix changes --- p.49Chapter 4.1.2 --- Problem Nature --- p.51Chapter 4.1.3 --- Imaging system setup --- p.52Chapter 4.1.4 --- Camera Calibration[13] --- p.52Chapter 4.2 --- Methodology --- p.54Chapter 4.2.1 --- Invariance measure --- p.54Chapter 4.2.2 --- The Geometric meaning of the Biplanar Disparity matrix --- p.58Chapter 4.3 --- RANSAC-Random Sample Consensus --- p.64Chapter 4.3.1 --- finding Homography matrix by using RANSAC[72] [35] --- p.64Chapter 4.3.2 --- finding Fundamental matrix by using RANSAC[73] [34] --- p.65Chapter 4.4 --- Harris Corner detection --- p.65Chapter 5 --- Simulation and experimental results --- p.67Chapter 5.1 --- Simulation experiments --- p.67Chapter 5.1.1 --- Preliminary experiments --- p.67Chapter 5.1.2 --- Specification for the synthetic data system --- p.71Chapter 5.1.3 --- Allowed error in the experiment --- p.71Chapter 5.2 --- Real images experiments --- p.72Chapter 5.2.1 --- Experiment instrument --- p.72Chapter 5.2.2 --- The Inspection Procedure --- p.74Chapter 5.2.3 --- Images grabbed under above system --- p.75Chapter 5.2.4 --- Experimental Results --- p.81Chapter 6 --- CONCLUSION AND FUTURE WORKS --- p.83Chapter 6.1 --- Summary on the contribution of my work --- p.83Chapter 6.2 --- Some Weakness of The Method --- p.84Chapter 6.3 --- Future Works and Further Development --- p.84Chapter 6.3.1 --- About the synthetic experiment --- p.84Chapter 6.3.2 --- About the real image experiment --- p.85Bibliography --- p.8

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications

Spectral Energy Distribution Modeling of Markarian 501 through a non-linear least square minimization

So far the Spectral Energy Distribution (SED) of Active Galactic Nuclei (AGN), in particular blazars, have been obtained in a heuristics way. This is mainly due to both the many free parameters of the emission model and the severe lack of simultaneous multi-frequency data. This leads to non-rigorous and possibly biased analyses, and makes it difficult to compare results coming from different analyses. However, recent simultaneous multi-frequency campaigns are providing long-term broad-band coverages of source activity, and large multi-frequency data sets are becoming available. So emission model fitting may be attempted with better profit now. The main aim of this thesis is to develop a statistical approach that fits AGN SEDs in a rigorous way. Such an approach consists in a Chi squared -minimization, based on the Levenberg-Marquardt algorithm, that returns the most likely values of the SED parameters, plus a method devised to obtain the related uncertaintes. The whole minimization process is implemented in a C++ code. However, this approach may reveal unexpected features of the Chi squared-manifold that might affect convergence, due to spurious correlations between model parameters and/or inadequacy of the currently available datasets. For these reasons, a statistical analysis will be carried out on the solutions obtained from several minimizations, each starting from different points of the parameter space. This approach is applied to different activity states of the blazar Markarian 501, in a Synchrotron Self Compton (SSC) framework. In particular, starting from available observations of this source taken with the ground-based Major Atmospheric Gamma-ray Imaging Cherenkov telescopes (MAGIC) in 2011, 7 multi-frequency datasets were obtained. Based on multi-frequency and simultaneity requirements, all datasets include also data provided by the Swift UVOT, Swift XRT, and Fermi LAT orbiting telescopes. The SED modelling of each dataset will be performed through a non-linear Chi squared-minimization in order to obtain the most likely values of the parameters describing the SSC model. Finally, it is worth remarking that this approach is not only a rigorous statistical method to find the most likely source parameters for different scenarios, but it also represents a powerful tool to efficiently discriminate between different emission models

Comets as natural laboratories: Interpretations of the structure of the inner heliosphere

Comets can be considered to be natural laboratories of the inner heliosphere, as their ion tails trace the solar wind flow. Much has been learnt about the heliosphere’s structure from in situ solar wind spacecraft observations. Their coverage is however limited in time and space. This thesis proposes to address these constraints and ascertain the validity of analysing comets’ ion tails as complementary sources of information on dynamical heliospheric phenomena and the underlying continuous solar wind. Solar wind conditions influence comets’ induced magnetotails, formed through the draping of the heliospheric magnetic field by the velocity shear in the mass-loaded solar wind. I present a novel imaging technique and software to exploit the vast catalogues of amateur and professional images of comet ion tails. My projection technique uses the comet’s orbital plane to sample its ion tail as a proxy for determining radial solar wind velocities in each comet’s vicinity. Making full use of many observing stations from astrophotography hobbyists to professional observatories and spacecraft, this approach is applied to several comets observed in recent years. Complementary velocities, derived from folding ion rays and a velocity profile map built from consecutive images, are provided as an alternative means of quantifying the solar wind-cometary ionosphere interaction. I review the validity of these techniques by comparing near-Earth comets to solar wind models in the inner heliosphere and extrapolated measurements by ACE to a near-Earth comet’s orbit. My radial velocities are mapped back to the solar wind source surface to identify sources of the quiescent solar wind and heliospheric current sheet crossings. Comets are found to be good indicators of solar wind structure, but the quality of results is strongly dependent on the observing geometry. Many ion tails also show a constant curvature, so far unexplained, which further complicates the interpretation of tails’ orientations