We assume a number of points X," on straight line
features of the "as is" object being measured. We only
know the "blueprint" expressions for these straight lines:
E,® s [E.? 4 $,.Cos o.Cosf],,
N,? z [N,? « S,Sin a.Cosf],,,,, (2)
HP = He * S,Sin fli,
Where:
S, -the distance of point A from reference point 0;
a and B = the azimuth and vertical angles of the straight
line feature, respectively (Fig. 2). In matrix notation this
becomes:
XP? =x? +S, TRIG (3)
Where:
Cos a.Cos p
TRIG = Sin a.Cos B
Sin p
For every measured point A on a line of the "as is" model,
three observation equations can be formulated for the
seven unknowns, A, AX, R of the transformation (1), and
the one additional unknown S, locating the point A on the
line:
X," = ARX,P + AX
Where:
X? - X? S A.TRIG
The unknown transformation parameters, and the additional
point unknown, S, may be determined from these
equations by standard least squares adjustment, if sufficient
measurements are available.
How many measurements are needed to arrive at a unique
solution to the problem? Let us assume we measure N
points in the "as is" system, this gives 3N observation
equations for the 7+N unknowns, leading to the inequality:
3N>7+N. (4)
At least four points have to be measured in the "as is"
system in order to arrive at a unique solution for the
system. These four points obviously need to be positioned
on at least two linear features in order to avoid singularities.
We may, for example, measure two points each on two
linear features.
J qu
qu P. A o
5, N y N
fi
line 1
JI
aman"
Xo»
ULL
ine 2
o denote measured points x,
Figure 2. Absolute orientation:
Determination of the transformation parameters from
one coordinate system to another using straight line
features only.
We may verify our conclusions with the following example:
We wish to find the transformation parameters between the
coordinate system of a cube in object space and its blue
print shape.
line 2
688
Figure 3: Exemplification of Absolute orientation Problem
Measuring only one line A on both cubes, does allow us to
rotate the object cube into the blue print space, but we
know neither its position along that line, its orientation with
respect to the line nor its scaling. Measuring the two
rectangular lines A and B, the object cube can now be
positioned and oriented, but we cannot determine the scale
factor between object and blue print space. Only when
measuring two non-coplanar lines A and C, can the scale
factor also be determined and the absolute orientation
problem completed.
4. RELATIVE ORIENTATION USING EDGES
We start from the well known projective relationships
(American Society of Photogrammetry, 1980) relating the
object space to the image space:
Xf! - P (X, , Ya) ) (5)
Where:
X, 2 vector of image coordinates (x,y) of point A in image
(1);
X, = vector of model coordinates (E,N,H) of point A;
Ya 7 Vector of 6 parameters of image (1); being the tilts, 6,
0, x and projection centre coordinates (E,N,H);
P = projective relationship.
In relative orientation using edges we assume that points
on linear features are measured monoscopically both in the
left and right image. Non homologous points are observed,
that is, points on the linear feature measured in the left
image differ from those in the right image. This will usually
be the case in automatic industrial metrology, and no online
image correlation is required.
The following observation equations can be formulated for
two points A and B measured on one and the same linear
feature of the object:
Left image:
x" zP(X,; Y O) (6)
X,= X, + S, TRIG
Right image:
X= P (Xs ; Yo ) (7)
X, 2 X, * S,. TRIG
The image parameters of the left image are set to zero.
Five parameters of the right image are unknown after
choosing a suitable model base.
In addition, for every linear feature in model space, there
are five unknowns: the three coordinate values X, of one
reference point on the line, and two directions a, B (Fig. 4).
Also, for every measured point, the distance S from the
reference point X, is unknown. (For the first point
measured on a new line, say point A, we choose S to be
zero.)