International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
geologic), the output metric values would have been much 
higher (over 0.8). 
Generally, from the qualitative and quantitative comparison of 
the HOUGH Transform by Fitton-Cox and the edge detection 
algorithms it is inferred that edge detection algorithms perform 
better in terms of Pratt quantitative evaluation, while the 
HOUGH Transform is superior concerning the Rosenfeld 
metric. The latter makes sense because the modified HOUGH 
Transform algorithm extracts fully connected lines using pixels. 
Furthermore, the performance of the Fitton-Cox algorithm is 
characterized by a localization problem, meaning that the 
extracted lines are not accurately localized comparatively to the 
edge detection algorithms and, the length of the extracted lines 
is fully dependent on the selection of the input parameters. On 
.the other hand, a line is what the photointerpreters represent a 
lineament with, and not a curvilinear segment. 
3. CONCLUSIONS 
One main aspect from applying the edge detection algorithms is 
the capability of extracting segments that really follow the 
terrain topography. This leads to the extraction of the exact 
shape of the geomorphologic features, as the caldera in this 
case. Taking also into consideration that these algorithms 
perform well in terms of coherence, edge localization and high 
edge response, the implementation of edge detection algorithms 
provides useful means towards automated lineament mapping. 
Finally, the HOUGH Transform is quite useful for line 
extraction, but it requires a proper parameter setting and 
adjustments to be applicable in different terrain and 
illumination conditions of natural scenes when applied to 
satellite data. Its performance to the Digital Elevation Model 
could be further investigated. 
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