# Full text: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

```International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999
by a dynamic split algorithm (Stilla et al., 1996). This
vectorization step may profit from the MDL-principle (c.f.
Weidner and Forstner, 1995)
4.3. Sloped Roofs
In order to test the hypothesis for case (iii), the gradient field of
the elevation image (Fig. 7) is calculated. From the orientation
of the gradients possessing a minimum value, a histogram is
determined (Fig. 8). In this histogram, we search for peaks to
determine major orientations and orientation intervals around
them.
These segments of homogeneous oriented gradients may still
contain areas of different slopes. To separate such connected
areas, the histogram of the slope is determined. If the
distribution shows several significant peaks essentially differing
in slope, then the segment is split into the corresponding areas.
If the histogram does not show a few major orientations, local
relations have to be considered. Several segmentation
algorithms that are based on region growing are described and
compared in Hoover et al. (1996).
Out of the segments of homogenous orientation and slope,
spatial planes are calculated by a least square fit. Recalculating
the z-coordinate for the contour points by the plane equation,
we ensure a planar 3D contour chain (Fig. 10).
Fig. 7. 3D view of elevation data of a single building and the
corresponding histogram.
By thresholding the orientation image (Fig. 9 left) at the
boundaries of the orientation intervals, segments of similar
orientation are separated (Fig. 9 right). The areas resulting from
the segmentation are then morphologically dilated and eroded
to fill small unknown enclosed areas, remove small holes, and
separate components, which are connected only by few pixels.
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Fig. 10. 3D contours of roof segments.
A polygonal description is obtained by deleting points of the 3D
contour chain. Special attention is required at the common
edges of neighboring segments so that they form a single line.
Since edges of neighboring segments do not intersect in exactly
one point, a common vertex has to be calculated.
Fig. 8. Histogram of gradient orientation.
Fig. 11. Reconstructed sloped roof structure.
5. UPDATE OF CITY MODELS
For updating databases of 3D-city models, we propose a
procedure in two phases. In a verification phase, the buildings
that are already stored in the database are compared to the new
elevation data by histogram characteristics. They are confirmed,
modified or deleted.
Fig. 9. Image of gradient orientation and segmented elevation
image.
In a classification phase, new buildings are searched in the
elevation data of non-buildings. The discrimination of artificial
objects from natural objects can be achieved taking into account
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