International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
3.2 Methodology
The main steps followed in the proposed damage assessment
method are illustrated in Figure 3. First, the post-event aerial
photograph of the area was pre-processed using histogram
equalization technique to provide better discrimination between
the buildings and their shadows. Next, the buildings were
selected one-by-one using the vector building boundary
information. Then, for each building, the shadow-producing
edges were determined. To do that, a simple algorithm was
developed. The illumination angle was available from a previous
study conducted by San (2002) as 135? from the x-axis. A buffer
zone was generated along the shadow edges of the buildings.
This was followed by the execution of the watershed
segmentation algorithm. For each building, a binary-colored
output representing the shadow and non-shadow areas was
generated. Finally, the accuracy assessment was carried out by
comparing the analyzed buildings with the reference data.
Post-event Vector
Aerial Building
Photograph Boundaries
Shadow Edge
Detection «—
Building
Selection
Buffer Zone
Generation
Watershed
Segmentation
Building
Condition
Assessment
Figure 3. Damage detection using watershed segmentation
3.2.1 Building Selection and Shadow Edge Detection:
To select the vector building polygons, each polygon was
assigned a unique identification code. In addition, the edges of
cach polygon were also given numerical codes. The edges and
the corresponding (x, y) coordinates of a building (#175) are
illustrated in figure 4. The labeling of the edges was necessary to
identify the shadow casting edges of a building being assessed
and to relate these edges with the corresponding shadows.
Edge
x Y Number
230 419 1
239 398 1
239 424 4
230 419 4
249 402 3
2/39 424 f
240 398 2
249 402 2
(a) (b)
Figure 4. (a) The edges of building 4175 and (b) The format of
vector data
After selecting a building, a minimum-bounding rectangle was
generated using the vector information by finding the minimum
and maximum x-y coordinates (totally four points). Then, these
points were connected to each other and the minimum-bounding
rectangle was constructed. A buffer bound was then generated
via expanding the minimum-bounding rectangle from its edges
about six pixels. The bound was created in order to take into
account the shadow regions produced by the buildings. Next, the
shadow producing edges of the selected building were detected
using a simple algorithm. The algorithm works as follows. The
corner points are found from the vector information. This is
simply finding the points that share the same end point on
adjacent edges. For example, since both edge 4 and edge 1 share
the same end point, (x=230,y=419), this end point is selected as
a corner point (Figure 4b). Then, the Euclidean distances (di, d»,
d; d), shown in figure Sa, are computed between the corner
points of the building and the corner of the minimum-bounding
rectangle in the illumination direction. The computed distances
are then sorted. If there is only one maximum distance, the edges
that contain the same corner point are selected as the shadow
edges. If on the other hand, there are two maximum distances
then, the edge that contains those corner points is the shadow
edge. These two cases can be illustrated with an example. If d; >
d, » d; » d;, then the shadow edges are determined as edge 1 and
edge 2 (figure 5b). This is because the corner point connecting
these edges possesses the farthest distance (d,). If the ranking is
d, = d, > d, > d,, then edge 1 is selected as the shadow edge
since it is the only edge containing the farthest distances d, and
du.
di [-
Shadow E = Edge 2
producing 3 d
edges
Edge
A Ca A Anleof
es illumination
(a) (b)
Figure 5. (a) The Euclidean distances and the angle of
illumination. (b) The shadow producing edges of building # 175
644
Inter
3.2.2
A t
shad
divic
builc
was
the |
purp
shad
of tl
signi
Bu
(
buil
Figur
edge:
3.2.3
The
of fl
sour
need
regic
segn
and
builc
respe
rand
orier
The
binai
regic
to sl
area:
in bl
M:
fa
ar
Figur
trans
trans