ves of the Photogrammetry, Remote
International Archi
is somewhat true as long as proper focusing and image
processing techniques are used wisely (Soucy et al., 1990).
Nonetheless, one should remember that the underlying
hypothesis of active optical geometric measurements is that the
imaged surface is opaque and diffusely reflecting. Hence, not
all materials can be measured accurately like vapour-blasted
aluminium (VBAI). Problems arise when trying to measure
glass, plastics, machined metals, or marble (see Figure 6). As
reported by Godin et al. 2001, marble departs from this
hypothesis, and exhibits two important optical properties in this
context: translucency, and non-homogeneity at the scale of the
measurement process.
Figure 6. Laser spot projected on a marble surface.
This structure generates two key effects on the geometric
measurement: a bias in the distance measurement, as well as an
increase in noise level, when compared to measuring a
reference opaque surface like VBAI. They show results for
triangulation-based laser scanners. With their system, they
estimated the bias to be about 25-30 um and the range
uncertainty rises from 10 pm on VBAI to 25-50 um according
to the spot size (as with many similar commercial systems).
In another experiment, a flat piece of VBAI and a marble area
on a pedestal were m sasured conducted using both a FMCW
system (see Section 2.1.2) and a triangulation laser scanner (see
Section 2.1.1). In both cases, a plane equation was fitted using
the same algorithm. The FMCW system gave 14 um on VBAI
and on marble, 87.6 um (both at a distance of 4 m). The laser
triangulation system gave 30 um on VBAI and on marble, 49
wm (at a distance 30 cm). This last system follows the results
presented in Godin et al., 2001. The FMCW behaved in a
surprising way! Additionally, the type of feature being
measured is an important factor affecting the accuracy of a
machine vision system. The accuracy of active 3D cameras
drop when measurements are performed on objects with sharp
discontinuities such as edges, holes, and targets (Soucy et al.,
1990; Wallace et al., 1999; Bochler et al., 2003). This means
that systems based on only range will not provide sufficient
data for these applications (El-Hakim et al, 1994). The
following is a list of concerns encountered with laser scanners
(and 3D vision system in general):
e Occlusions/Shadows
eo Abrupt texture and
(Buzinski et al., 1992)
e Laser finite footprint and spread on sloped surfaces
e Specular reflections (Fisher et al. 1993)
e Motion: scene, object, ambient vibrations
Therefore, selecting a vision system for a particular application
must take into account the ability of the system to measure the
features of interest with the required accuracy. Many
applications (like found in cultural heritage) do not allow any
alterations to the object to suit the vision system, €.g. by
placing markers or changing the reflectivity of the surface.
shape variations: Edge curl
Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
3.4 Calibration and standards
A measurement result has only a meaning if its uncertainty is
known no matter if it is large or small compared to others. Here
we give a famous quotation taken from Lord Kelvin: “When
you can measure what you are speaking about, and express it in
numbers, you know something about it; but when you cannot
measure it, when you cannot express it in numbers, your
knowledge of it is of a meagre and unsatisfactory kind: it may
be the beginning of knowledge. but you have scarcely, in your
thoughts, advanced it to the stage of science." - Sir William
Thompson, Lord Kelvin (1824-1907). It should summarize the
importance of knowing how a 3D system measures physical
quantities.
The statement of uncertainty is usually based on comparisons
with standards traceable to the national units (SI units). For
example, standards are available to manufacturers of theodolites
and CMMs for assessing their measuring systems. A guideline
called VDI/VDE 2634 has been prepared in Germany for
particular optical 3D vision systems. It contains acceptance
testing and monitoring procedures useful for evaluating the
accuracy of optical 3D measuring systems based on area
scanning. The guideline applies to optical 3D measuring
works according to the principle of
fringe projection, moiré techniques and
systems, which
triangulation, e.g.
photogrammetric/scanning systems. Though no internationally
recognised standard or certification method exists to evaluate
the accuracy, the resolution, the repeatability, the measurement
uncertainty of laser range cameras, the user should devise
techniques to ensure a confidence level on what is being
measured. Definitions of terms can be found in the VIM
standard for metrology (VIM 1993). The user should still
perform periodic verifications even if the manufacturer provides
a specification sheet. Studying scientific literature published on
testing range cameras and attending conferences like this one
should help in preparing a verification methodology that best
suit the user's needs. Boehler et al. 2003 and Johansson 2002
present detailed experimental results on different laser scanners.
In practice, an object that is distinct from the calibration
equipment and for which the accuracy is ten times better than
that of the range camera will be employed in such an
evaluation. A laboratory can be dedicated to calibration and
evaluation of machine vision sensors and systems. The main
objectives could be
e to perform precise calibration of various types of
sensors and systems,
e to monitor sensor stability over time and under
variations in environmental conditions such as
temperature and ambient light,
. to evaluate system geometric measurement accuracy
on a wide range of specially designed standard
objects and high-precision positioning devices, and,
e to validate computer vision algorithms, such as target
and edge measurement, multi-view registration,
model-based recognition, and sensor fusion.
Unfortunately, it is not always possible to own and maintain
such a facility. Furthermore, bringing à verification object
(especially if it has to be accurate) to a remote site could be
difficult.
978
Int
Prc
cat
tex
cot
gec
vol
CA
trai
ort]
resi
4.1
As
sur
esti
unc
satu
witl
low
(Fig
Sup]
ord
nov
men
Figure
triangi
Donat
scan a
satura
4.2
Like
Thre:
inspe
three
Ther:
worl
the fi
whicl
of Se
(scier
Meto
two ¢
an ex
and «
repres
produ
3D in
only