[GRASS-dev] Introduction and GSoC

Moritz Lennert mlennert at club.worldonline.be
Mon Apr 2 07:42:20 EDT 2012

On 30/03/12 23:56, Eric Momsen wrote:
> I am reading more about image classification (from
> http://grass.osgeo.org/wiki/GRASS_SoC_Ideas ):
> 4. Implement image segmentation algorithms and tools
> 5. Implement region-based classification
> 6. Implement hierarchical classification tools (e.g. being able to
> create a large class "forest", with subclasses of different types of
> forests)
> I see Hamish is interested in mentoring the parallelization portion of
> that list.  Are these other ideas orphans, or is someone available
> that could discuss the background and needs of the community around
> these ideas (and/or mentor...)  Thanks!

I'm the one who added these idea to the list as I see that this is one 
of the reasons colleagues do not adopt GRASS. However, I'm not an expert 
in the matter and am not sure I would be very helpful as mentor 
(although I'm willing to try).

Concerning the ideas:

4. Currently GRASS does not provide any image segmentation as such. 
i.smap contains image segmentation in its process, but the user cannot 
get segmented outputs. Many algorithms exist and its an ongoing field of 
research. FLOSS software that provide such algorithms include Orfeo 
Toolbox (OTB), SAGA, R, Sextante (?) and probably a whole series of 
others. I think the implementation of a series of such algorithms could 
be a project on its own.

5. One of the main applications of image segmentation today is in 
region-based classification of very high resolution imagery. As with 
current resolutions individual objects are composed of many pixels, it 
is often more efficient to first identify "objects" or homogeneous 
multi-pixel regions in the image through segmentation and then to 
classify these regions. OTB provides this I think, but I don't know if 
any other FLOSS software does. 5 depends on 4, so it is only possible if 
4. is limited to the strict minimum in terms of segmentation algorithms 
and then focus is put on 5. Maybe a bit too ambitious.

6. In the current classification algorithms in GRASS each designated 
class of pixels is on the same hierarchical level as others. However, it 
is often interesting to provide the option to classify an image first in 
a rough manner into a series of base classes (built-up, vegetation, 
naked soils) and then to refine classification within each of these 
classes (e.g. built-up into high-density / low-density, vegetation into 
forest, grasslands, etc), but to keep the hierarchy, i.e. to allow 
extracting an image (and a legend) of the classification at each level.

Hope this helps and maybe motivates others to join-in as mentors.


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