Extracting 3D parametric curves from 2D images of Helical objects

Helical objects occur in medicine, biology, cosmetics, nanotechnology, and engineering. Extracting a 3D parametric curve from a 2D image of a helical object has many practical applications, in particular being able to extract metrics such as tortuosity, frequency, and pitch. We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. The results show that the extracted 3D curve comes within close Hausdorff distance to the ground truth, and has near identical tortuosity for helical objects with a circular profile. Parameter insensitivity and robustness against high levels of image noise are demonstrated thoroughly and quantitatively

Review of the mathematical foundations of data fusion techniques in surface metrology

The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

Characterization of the accuracy in a reverse engineering process employing white light scanned data to develop constraint-based three dimensional computer models

The statistical accuracy of constraint-based three-dimensional (3D) models created using reverse engineering software to post process scan data collected by an Advanced Topometric Sensor (ATOS) system is currently unpublished information useful to the end-user. Throughout the process of scanning an object and converting the scanned data into a constraint-based 3D model, error can be introduced into the final model. The error introduced into the constraint-based 3D model is difficult to calculate due to a large number of variables and factors. The current study sought to characterize the accuracy of this process based on different measurement volumes and object sizes. Optical 3D metrology techniques have become an accepted method in the field of reverse engineering. The popularity of optical 3D metrology is due in large part to the non-contact approach, which can quickly produce a dense point cloud. Using post-processing software, these point clouds can be converted into a constraint-based 3D model and used in much the same manners as 3D models created using CAD software. To simulate a variety of measurement conditions, four measurement volumes and three object sizes were selected generating a total of 36-point clouds. The 36-point clouds were converted into constraint-based 3D models. Four measurements were collected from each 3D model. To analyze the data collected, hypothesis testing was conducted to compare the data and inferential statistics were applied. The statistical tests include one-sample t-tests, two-sample t-tests, a General Linear Model (GLM), and multiple 1-way ANOVA. The statistical test found that a difference existed between the measured values and the actual values for both the object size and measurement volume

Hybrid Functional-Neural Approach for Surface Reconstruction

ABSTRACT. This paper introduces a new hybrid functional-neural approach for surface reconstruction. Our approach is based on the combination of two powerful artificial intelligence paradigms: on one hand, we apply the popular Kohonen neural network to address the data parameterization problem. On the other hand, we introduce a new functional network, called NURBS functional network, whose topology is aimed at reproducing faithfully the functional structure of the NURBS surfaces. These neural and functional networks are applied in an iterative fashion for further surface refinement. The hybridization of these two networks provides us with a powerful computational approach to obtain a NURBS fitting surface to a set of irregularly sampled noisy data points within a prescribed error threshold. The method has been applied to two illustrative examples. The experimental results confirm the good performance of our approach.This research has been kindly supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project ref. no. TIN2012-30768, Toho University (Funabashi, Japan), and the University of Cantabria (Santander, Spain)

3D modeling of cultural heritage objects with a structured light system

3D modeling of cultural heritage objects is an expanding application area. The selection of the right technology is very important and strictly related to the project requirements, budget and user's experience. The triangulation based active sensors, e.g. structured light systems are used for many kids of 3D object reconstruction tasks and in particular for 3D recording of cultural heritage objects. This study presents the experiences in the results of two such projects in which a close-range structured light system is used for the 3D digitization. The paper includes the essential steps of the 3D object modeling pipeline, i.e. digitization, registration, surface triangulation, editing, texture mapping and visualization. The capabilities of the used hardware and software are addressed. Particular emphasis is given to a coded structured light system as an option for data acquisition.Publisher's Versio

Optical measurement of shape and deformation fields on challenging surfaces

A multiple-sensor optical shape measurement system (SMS) based on the principle of white-light fringe projection has been developed and commercialised by Loughborough University and Phase Vision Ltd for over 10 years. The use of the temporal phase unwrapping technique allows precise and dense shape measurements of complex surfaces; and the photogrammetry-based calibration technique offers the ability to calibrate multiple sensors simultaneously in order to achieve 360° measurement coverage. Nevertheless, to enhance the applicability of the SMS in industrial environments, further developments are needed (i) to improve the calibration speed for quicker deployment, (ii) to broaden the application range from shape measurement to deformation field measurement, and (iii) to tackle practically-challenging surfaces of which specular components may disrupt the acquired data and result in spurious measurements. The calibration process typically requires manual positioning of an artefact (i.e., reference object) at many locations within the view of the sensors. This is not only timeconsuming but also complicated for an operator with average knowledge of metrology. This thesis introduces an automated artefact positioning system which enables automatic and optimised distribution of the artefacts, automatic prediction of their whereabouts to increase the artefact detection speed and robustness, and thereby greater overall calibration performance. This thesis also describes a novel technique that integrates the digital image correlation (DIC) technique into the present fringe projection SMS for the purpose of simultaneous shape and deformation field measurement. This combined technique offers three key advantages: (a) the ability to deal with geometrical discontinuities which are commonly present on mechanical surfaces and currently challenging to most deformation measurement methods, (b) the ability to measure 3D displacement fields with a basic single-camera single-projector SMS with no additional hardware components, and (c) the simple implementation on a multiple-sensor hardware platform to achieve complete coverage of large-scale and complex samples, with the resulting displacement fields automatically lying in a single global coordinate system. A displacement measurement iii accuracy of ≅1/12,000 of the measurement volume, which is comparable to that of an industry-standard DIC system, has been achieved. The applications of this novel technique to several structural tests of aircraft wing panels on-site at the research centre of Airbus UK in Filton are also presented. Mechanical components with shiny surface finish and complex geometry may introduce another challenge to present fringe projection techniques. In certain circumstances, multiple reflections of the projected fringes on an object surface may cause ambiguity in the phase estimation process and result in incorrect coordinate measurements. This thesis presents a new technique which adopts a Fourier domain ranging (FDR) method to correctly identifying multiple phase signals and enables unambiguous triangulation for a measured coordinate. Experiments of the new FDR technique on various types of surfaces have shown promising results as compared to the traditional phase unwrapping techniques