typical example of obtained results. 
  
Fig. 6: A portion of a SPOT panchromatic image, with 
marked seed points and potential problematic areas 
  
Fig. 7: Wavelet transformed image 
Specifically, Fig. 6 depicts a portion of a SPOT pan- 
chromatic image of Moudon, Switzerland. On it, 
marked by black discs, one can distinguish the seed 
points provided by the operator along the road which 
is to be extracted. The white rectangles denote po- 
tential problematic areas, i.e. intersections with other 
roads which might cause an erroneous change of di- 
rection, and increased radiometric noise and ambi- 
guities due to passage through an urban area. Fig. 7 
shows the wavelet transformed image. It is apparent 
that the transformation has made the existing road 
network appear more prominently, thus facilitating 
the subsequent extraction of the road of interest, the 
result of which is shown in Fig. 8. It can be easily ob- 
served that no problems were finally encountered in 
its extraction despite the presence of the aforemen- 
tioned problematic areas. Additional experiments 
with other types of potential problems (e.g. gaps, low 
texture) verified the efficiency and effectiveness of 
the technique. 
  
Fig. 8: The semi-automatically extracted road 
We have also successfully implemented least 
squares template matching and Fig. 9 presents at 
left a typical example of edge tracking by this method. 
Matching has been initiated at the top of the white 
dotted line and proceeded downwards. White dots 
denote the resulting edge positions. Edge tracking 
Stopped at the bottom of the dotted line (position 
marked by white circle) because it reached a corner, 
and as previously discussed this caused matching to 
fail and tracking to stop. 
  
Fig. 9: Least squares template matching results 
The right side of Fig. 9 shows the application of this 
method for the extraction of several edge segments 
of an object and demonstrates cases of distraction or 
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