Hello Peter,
On 23/11/07 08:49, Peter Löwe wrote:
The issue about how to emulate the eCog-approach into GRASS has been
around for a while. Here are my two eurocents of knowledge:
eCog consists of several algorithms. First, a segmenting tool
(patented...) is used to divide a multispectral image stack into
segments. Then, a knowledge-based (fuzzy) merging process gets you to
the object-representation.
So to do it with GRASS, we need to have a multispectral segmenting
tool plus "the object stuff".
I am not sure if there are any FOSS-segmenting tools in the works
that do their job without signature files [medical imaging tools,
maybe?].
I have the feeling that this is the most important part.
For the next step, the abstraction from spatial segments to objects,
object-oriented grass-friendly environments such as R or CLIPS/CAPE
could be used to create a prototype/demonstrator. However, the
performance for large data-sets might be significantly below a c/c++
implementation.
Is this automatic in eCognition or does it demand user input ? If the
latter and IIUC, the main challenge here is a fuzzy classification
algorithm, or ? Implementations of that shouldn't be too difficult to find.
Thanks for your explanations.
Moritz
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