tep is to
etwork.
>xtracted
ited very
gful and
en from
dditional
the lines
1odule II
the road
Sect. 4.2
accuracy
of local
1e elimi-
asically,
Thus, it
egments
nostly is
iodule II
to their
II and
xtracted
: possi-
odule I.
Module II then returns all parts of its road network to module I
which are not covered by the "good" segments. From this result
module I gets information about the good segments which might
be linked according to global grouping criteria, and it can easily
decide which of the “bad” segments should be labeled as important
for the connectivity of the road network. This procedure is invoked
before every elimination step of module I.
Because the local grouping of module I bridges gaps between the
road segments, relaxes its grouping thresholds, and can rate other
road segments as "good" or "bad" ones, also the seed pairs for mod-
ule II can change. Therefore, it is necessary that module I asks
module II before every elimination step again.
In Fig. 7 this process is exemplified for an early elimination step:
The road segments displayed in white are considered to be “good”.
Candidates for elimination are displayed in black. The paths re-
turned by module II are dotted white lines. In this example the
overlap with a global path prevents some short road segments with
a bad rating from being eliminated.
Considering, that module I is quite good at detecting correct parts
of the road network, and that module II is able to provide good
hypotheses for the global connectivity, both modules benefit from
this combination.
After the last elimination step all paths which were provided by
module II are added to the network extracted by module I. For those
paths which can not be verified using the methods of module I, at
least the position of the path is adapted to the features in the high
resolution image. This optimization is done, because the connec-
tion hypotheses from module II are known to be quite reliable, if
the seed pairs are well selected, and only the geometry of the paths
is known to be less accurate. The final result of this integration of
local and global grouping modules is given in Fig. 8.
5 EVALUATION
In the previous section we made some qualitative statements about
the results. Now, to get more imdependent statements we apply
a quantitative evaluation. For this evaluation we compare the ex-
tracted road networks with a reference network. The internal qual-
ity measures of module I and module II about parts of the extracted
road network are not taken into account. In the following we give a
short description of the external evaluation procedure we use. For
more details see (Heipke et al., 1998, Wiedemann, 1998). The ref-
erence data for this evaluation is shown in Fig. 9. It was manually
plotted at a resolution of 0.25 m. The width of the roads in the
reference network ranges from about 3 m to 8 m.
The evaluation scheme allows for statements about the complete-
Albert Baumgartner
i a. IA |a. fos d
Figure 7: Detail: Global link hypotheses (dot-
ted, white) and road segments (start segments for
global grouping are white, others, black).
Figure 8: Results of integrated combination of lo-
cal and global module
ness and the correctness of the extracted roads by matching the extracted data to the reference data using the so-called
"buffer method". For the correct parts of the extracted roads it provides further an RMS-value of the position of the
extracted axes with respect to to manually plotted reference. The completeness indicates how much is missing in the
network. whereas the correctness is related to the probability of an extracted linear piece to be indeed a road.
Completeness is defined as the percentage of the reference data that is explained by the extracted data, i.e., the percentage
of the reference data which lies within the buffer around the extracted data.
The correctness represents the percentage of correctly extracted road data, i.e., the percentage of the extracted data that
lies within the buffer around the reference network.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 63