Stefan Hinz 
  
extracted roads, again, and new connections are hypothesized. This process iterates until no more connections are found 
to be correct. 
4.2 Preliminary results 
In the first phase of realization of the proposed concept, we focused 
on one hand on the context-based data analysis, in particular, the 
segmentation of Regions of Interest (Rol) and the delineation of 
approximate position and direction of potential roads, since context 
analysis plays a key role to reduce the scene complexity. On the 
other hand we implemented modules for the construction of lane 
segments based on the extraction and grouping of markings. For 
vehicle detection, some preliminary steps have been undertaken. 
By this, the contribution of small sub-structures and context ob- 
jects to road extraction could be investigated. In the following, an 
example is described which shows results that can be achieved with 
the modules implemented up to now. For implementation issues, 
we refer the reader to (Hinz et al., 1999). 
The first example shows imagery and DSM of the downtown area 
of Washington (DC) (— 20 cm, resp. 3 m resolution). Rols are 
segmented using the context relation that most buildings are higher 
than the road surface. Therefore, the parts that correspond to locally 
high regions in a DSM are removed from the image. The segmen- 
tation procedure compares a smoothed version of the DSM with the 
original DSM and removes regions where the height difference be- 
tween both data exceeds a threshold. Furthermore, approximately 
parallel building outlines are detected by searching for elongated 
valleys in the DSM. Figure 5 shows the down-sampled image, the 
DSM image, and the segmented image with the detected valleys. 
The results are then transformed to the original image resolution 
followed by the extraction of thin, bright lines. (see Fig. 6). 
Thereafter, an iterative graph-based grouping algorithm is applied 
to group the lines into extended linear objects according to per- 
ceptual principles: absolute and relative proximity of lines as well 
as their continuation (see Fig. 7 a) ). In regions, where the context 
analysis was able to find hypothetical road center axes from parallel 
building outlines, i.e., the valleys in the DSM, only marking groups 
are kept that show good parallelism with DSM-valleys. The group- 
ing procedure results in a set of unique and topologically consistent 
marking groups, from which hypotheses for lane segments are gen- 
erated. We first find parallel marking groups and define their medial 
axis as the lane axis. However, due to occluding vegetation or park- 
ing cars, we can rarely detect road markings at the road sides, even 
if they are painted there. Hence, we construct additional hypothe- 
ses for lane segments on those portions of each side of a particular 
marking group where no parallel relation to another group could be 
established. 
Finally, the hypotheses are validated: The surface of a lane segment 
should be homogeneous in the direction of a lane. In road regions 
where this criterion is not fulfilled, a car must be present. We there- 
fore check the radiometry of lanes in one pixel wide stripes along 
the respective lane axis. To this end, we shift a one dimensional 
mask over each stripe and calculate mean brightness and variance. 
Please note, that the lanes are not constrained to be straight, though 
win « vi az bans dua 
© Masked image with aen detected in DSM 
  
Figure 5: Context analysis with DSM 
  
(b) 
Figure 6: (a) DSM-valleys projected on image 
patch, (b) result of line extraction 
some generic knowledge about the geometry of lanes by means of lower bounds for their length and curvature is included 
(see, e.g., the upper left corner of Fig. 7 b). 
Homogeneous parts of a lane segment are labeled as "good" hypotheses, whereas larger portions with high variance 
indicate abnormal changes in the surface and are labeled as search regions for vehicles. Figure 7 b) visualizes se- 
lected bright and homogeneous lane segments, but no hypothesis is ultimately rejected at this point. Some of the 
  
410 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.