Within the context of the ASTM E57 working group WK12373, we compare the two methods that had been initially proposed for calculating the relative range error of medium-range (2 m to 150 m) optical non-contact 3D imaging systems: the first is based on a single plane (single-plane assembly) and the second on an assembly of three mutually non-orthogonal planes (three-plane assembly). Both methods are evaluated for their utility in generating a metric to quantify the relative range error of medium-range optical non-contact 3D imaging systems. We conclude that the three-plane assembly is comparable to the single-plane assembly with regard to quantification of relative range error while eliminating the requirement to isolate the edges of the target plate face.
Lateral resolution is a particularly challenging concept to quantify in triangulation-based three-dimensional (3-D) imaging systems. We present these challenges, then describe an artifact-based methodology for evaluating the lateral resolution of a triangulation-based 3-D imaging system that uses laser spots or laser lines. In particular, the response of a 3-D imaging system to a spatial discontinuity (step edge) has traditionally been modeled as a first-order linear system. We model the response of a triangulation-based laser imaging system to a spatial step edge from first principles and demonstrate that the response should be modeled as a non linear system. This model is then used as a basis for evaluating the lateral (structural) resolution of a triangulation-based laser imaging system.
We present a series of dimensional metrology procedures for evaluating the geometrical performance of a 3D imaging
system that have either been designed or modified from existing procedures to ensure, where possible, statistical
traceability of each characteristic value from the certified reference surface to the certifying laboratory. Because there
are currently no internationally-accepted standards for characterizing 3D imaging systems, these procedures have been
designed to avoid using characteristic values provided by the vendors of 3D imaging systems. For this paper, we focus
only on characteristics related to geometric surface properties, dividing them into surface form precision and surface fit
trueness. These characteristics have been selected to be familiar to operators of 3D imaging systems that use
Geometrical Dimensioning and Tolerancing (GD&T). The procedures for generating characteristic values would form
the basis of either a volumetric or application-specific analysis of the characteristic profile of a 3D imaging system. We
use a hierarchical approach in which each procedure builds on either certified reference values or previously-generated
characteristic values. Starting from one of three classes of surface forms, we demonstrate how procedures for
quantifying for flatness, roundness, angularity, diameter error, angle error, sphere-spacing error, and unidirectional and
bidirectional plane-spacing error are built upon each other. We demonstrate how these procedures can be used as part of
a process for characterizing the geometrical performance of a 3D imaging system.
The National Research Council of Canada (NRC) is currently evaluating and designing artifacts and methods to
completely characterize 3-D imaging systems. We have gathered a set of artifacts to form a low-cost portable case and
provide a clearly-defined set of procedures for generating characteristic values using these artifacts. In its current
version, this case is specifically designed for the characterization of short-range (standoff distance of 1 centimeter to 3
meters) triangulation-based 3-D imaging systems. The case is known as the "NRC Portable Target Case for Short-Range
Triangulation-based 3-D Imaging Systems" (NRC-PTC). The artifacts in the case have been carefully chosen for their
geometric, thermal, and optical properties. A set of characterization procedures are provided with these artifacts based on
procedures either already in use or are based on knowledge acquired from various tests carried out by the NRC.
Geometric dimensioning and tolerancing (GD&T), a well-known terminology in the industrial field, was used to define
the set of tests. The following parameters of a system are characterized: dimensional properties, form properties,
orientation properties, localization properties, profile properties, repeatability, intermediate precision, and
reproducibility. A number of tests were performed in a special dimensional metrology laboratory to validate the
capability of the NRC-PTC. The NRC-PTC will soon be subjected to reproducibility testing using an intercomparison
evaluation to validate its use in different laboratories.
Quality metrics quantify by how much some aspect of a measurement deviates from a predefined standard. Measurement quality evaluations of laser range scanner data are used to perform range image registration, merging measurements, and view planning. We develop a scanning method that uses laser range scanner quality metrics to both reduce the time required to obtain a complete range image from a single viewpoint and the number of measurements obtained during the scanning process. This approach requires a laser range scanner capable of varying both the area and sampling density of individual scans, but can be combined with view planning methods to reduce the total time required to obtain a complete surface map of an object. Several new quality metrics are introduced: outlier, resolvability, planarity, integration, return, and enclosed quality metrics. These metrics are used as part of a quality-based merge method, referred to here as a quality-weighted modified Kalman minimum variance (weighted-MKMV) estimation method. Experimental evidence is presented confirming that this approach can significantly reduce the total scanning time. This approach could be particularly useful for rapidly generating CAD models of real-world objects.
A protocol for determining structural resolution using a potentially-traceable reference material is proposed. Where possible,
terminology was selected to conform to those published in ISO JCGM 200:2008 (VIM) and ASTM E 2544-08
documents. The concepts of resolvability and edge width are introduced to more completely describe the ability of an
optical non-contact 3D imaging system to resolve small features. A distinction is made between 3D range cameras, that
obtain spatial data from the total field of view at once, and 3D range scanners, that accumulate spatial data for the total
field of view over time. The protocol is presented through the evaluation of a 3D laser line range scanner.
KEYWORDS: Laser range finders, Spatial resolution, Scanners, Strontium, Sensors, 3D metrology, Laser systems engineering, Image resolution, 3D scanning, Imaging systems
In this study, laser range scanner lateral resolution is investigated for laser range scanners. A standardized method is
proposed and demonstrated for quantifying the lateral surface resolvability of a laser range scanner through the use of an
appropriately-designed artefact. A new metric for lateral surface resolution, the limit of surface resolvability, is presented
and is obtained using what is referred to as the wedge test. The results of applying this metrics using this test method to
laser range scanners is also presented.
Quality metrics, within the field of laser range imaging, are used to quantify by how much some aspect of a measurement deviates from a predefined standard. Measurement quality evaluations are becoming increasingly important in laser range imaging for range image registration, merging measurements, and planning the next best view. Spatial uncertainty and resolution are the primary metrics of image quality; however, spatial uncertainty is affected by a variety of environmental factors. A review how contemporary researchers have attempted to quantify these environmental factors is presented, along with spatial uncertainty and resolution, resulting in a wide range of quality metrics.
We have developed a series of new quality metrics that are generalizable to a variety of laser range scanning systems, including
those acquiring measurements in the mid-field. Moreover, these metrics can be integrated into either an automated
scanning system, or a system that guides a minimally trained operator through the scanning process. In particular, we
represent the quality of measurements with regard to aliasing and sampling density for mid-field measurements, two issues
that have not been well addressed in contemporary literature. We also present a quality metric that addresses the issue of
laser spot motion during sample acquisition. Finally, we take into account the interaction between measurement resolution
and measurement uncertainty where necessary. These metrics are presented within the context of an adaptive scanning
system in which quality metrics are used to minimize the number of measurements obtained during the acquisition of a
single range image.
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