ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002
knowledge, image context, rules and models to restrict the
search space, treats each road subclass differently, checks the
plausibility of multiple possible hypotheses, therefore provides
reliable results. The system contains a set of image processing
tools to extract various cues about road existence, and fuses
multiple cues and existing information sources. This fusion
provides complementary and redundant information to account
for errors and incomplete results. Working on stereo images, the
system makes an early transition from image space to 3D object
space. The road hypothesis is generated directly in object space.
This not only enables us to apply more geometric criteria to
create hypotheses, but also largely reduces the search space, and
speeds up the process. The hypotheses are evaluated in images
using accumulated knowledge. Whenever 3D features are
incomplete or entirely missing, 2D information from stereo
images is used to infer the missing features. By incorporating
multiple knowledge, the problematic areas caused by shadows,
occlusions etc. can be often handled. Based on the extracted
roads the road junctions are generated, thus the system provides
an up-to-date road network for practical uses. We also present
in this paper the results of road extraction in benchmark tests
conducted independently by our project partner, and the results
on black and white image data provided by another national
mapping agency. The quantitative analysis using accurate
reference data is also presented. The comparison of the
reconstructed roads with such data showed that more than 93%
of the roads in rural areas are correctly and reliably extracted,
and the achieved accuracy of the road centerlines is better than
Im both in planimetry and height. This indicates that the
developed system can serve as an automatic tool to extract roads
in rural areas for digital road data production. We are currently
working on the derivation of reliability criteria for the extraction
results. Our future work will concentrate on road extraction in
cities and city centers.
ACKNOWLEDGEMENTS
We acknowledge the financial support for this work and for the
project ATOMI by the Swiss Federal Office of Topography,
Bern. We also thank the National Institute of Geography of
Belgium for letting us use their data for this publication.
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