On 22/11/07 16:46, Nikos Alexandris wrote:
The i.smap module ( http://grass.itc.it/grass63/manuals/html63_user/i.smap.html ) can be utilised for image segmentation. So I suppose you can use the segments for an object-based classification (!).
i.smap might be a step in the right direction. I think (but am really not an expert) one of the important elements of the eCognition approach, is this:
Just like the human mind, it uses the color, shape, texture and size of objects, as well as their context and relationships to draw the same conclusions and inferences that an experienced analyst would draw."
So (just thinking out loud), maybe one could create a training map with a farily high number of examples of the types of objects one is looking for, then submit this to i.smap, clump neighboring cells together with r.clump. This would then be something like the "objects". Then you could calculate a series of indicators for each of these objects (shape, texture, etc) using r.texture, r.le.*/r.li.* (?) etc, on the original RS bands and then submit all the resultant raster maps based on these objects to a classification...
However, IIUC, eCognition actually builds the objects already using these object criterions, probably using some algorithm which goes through different possible objects and then tests them against the object criteria to decide which objects to create.
Carlos, I'll look into terralib and see what is in there. Thanks for the hint.
Moritz _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
