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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
  
generating a sharp change of extracted road direction due to the 
temporally one-edge tracing. It has also problems at the region 
where the trees are (obstacles and shadows). In this field road 
segment coincides with one out of two road edges, instead of 
the road axis. It works quite good at the roads which have 
smooth curves, regular width and good contrast. 
4. CONCLUSIONS 
In this paper, roads are chosen as line features for digitizing 
from digital aerial photographs, because roads are the most time 
consuming features to digitize in photogrammetry. Two road 
extraction algorithms are applied to digitize roads from mono 
digital aerial photographs and the results are compared. 
Although they have some problems both of semi-automatic 
methods seems to be very advantageous for digitizing roads 
from digital aerial photographs because they can be much 
quicker than the fully human-based solution and the reliability 
and the precision can be also at a good level. 
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Bajcsy, R., and Tavakoli, M., 1976. Computer Recognition of 
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Gelb, A., 1974. Applied Optimal Estimation. MIT Press, 
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McKeown, D.M., and Denlinger, J.L., 1988. Cooperative 
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Nevatia, R., and Babu, K.R., 1980. Linear Feature Extraction 
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Vosselman, G., and Knecht, J., 1995. Road Tracing by Profile 
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