ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002
record
Figure 2 Choosed coordinate system
The method of random shift
The method is based on record averaging.
The principle of the method is based on the as best as
possible detection of relative positions of the record
according to one selected record (usually the selected
record is the first snapped) with the accuracy of the
one tenth of the pixel.
Using of records positions information they
are translated and rotated in the way that in selected
coordinate system all the objects of the scene have
identical coordinates for each snapped record of the
scene. When imagined the records as overlays, then it
is the same as translation and rotation of the overlays
to get a feeling that it is one overlay.
The neigbouring pixels parts sizes of the
record (label — the contributions) which cover the
actual pixel are determined and the weighted average
of color values of that contributions are calculated.
Figure 3 illustrates one of the possible cases. S is the
area of actual pixel, S;, S», S;, S, are areas of record
pixles parts which cover the actual pixel. I is the
contribution to resulting color value of actual pixel. /;,
I”, I; 1, are color values of record pixels overlapping
the actual pixel. Then it is valid:
SS TSUCS TS (1)
I =[*S; + 12S, + I* S; L* S; (2)
nd |
/ i
/ ™ D.
J MN cM
,
1 T > l4
$47 A p
| "^ K 8 IL y
\ > | 4. M
a Tm 2 L^ um
Figure 3 Contribution of the record to resulting color of
actual pixel
When by this means achieved record
contributions to the resulting intensity of actual pixel
are averaged through all suitable records, the actual
pixel color value is achieved.
For determination of relative position of the
record according to the first snapped two detection
objects are placed in the scene. After thresholding of
the records and successive localization of these
detection objects their centers of gravity are
calculated. This will help to determine the relative
positions of the records.
The determination of detection objects
In the next it is supposed that every detection
object is created by pixels with darker color as their
neighbours in the vicinity of detection objects.
The first thing to do is to isolate the detection
objects from the background. The one of the effective
and easy implementable methods fairly solving this
problem is the method of thresholding. All the pixels
lighter than certain threshold value are filled with
white color (the background color). The rest of them
have original color which is used in the calculation of
the weighted average in the determination of the
detection objects centers.
I suppose, that every detection objects is
continuous. Because the thresholded image can
contain in addition to detection objects others objects,
it is necessary to find the way how to ignore them. In
my application the detection objects are selected from
all the detected objects by interactive user
determination of one point from the detection object.
For detection of the areas of the detection objects
which are bounded by the background color I use the
method of the area filling (seed fill).
When I know which pixles belong to
detection objects I can determine its centers. Because
the quality of the result strongly depends on the
accuracy of the determination of that centers, for their
computation I use several methods.
1. The method of simple average, where the center is
the arithmetic average of the coordinates of all
detection object pixels.
1
TAX. 3
nz ; (3)
T -the coordinates of the detection object center
N - the number of pixels of the detection object
X; - the coordinates of the i-th pixel of the detection
object (17 1, ... N)
Q - the set of all detection object pixels
2. The method of simple weighted average, where
the center coordinates are calculated as the weighted
average of all detection object pixles and the weight of
every point of detection object is its color. E.g., in my
application the darker is the point the more important
it is in the calculation of the center.
1
FE== VAS (4)
v A
T - the coordinates of the detection object center
N, - the sum of weights of all the pixels of the
detection object
v;- the weight of the i-th pixel of the detction object
X; - the coordinates of the i-th pixel of the detection
object (17 1, ... N)
Q - the set of all detection object pixels
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