Dear Ghassem,
OTB do not provide a fully integrated environment for object-orientated
classification, but several bricks you put together to build a processing
chain.

You're right, the strength of the object-oriented approach is to mix
spectral, spatial, and contextual attributes during the classification
process. In my understanding there is no straight-forward solution in OTB
at the moment.
What you can do is to produce a multi-band image including your spectral
bands, but also new pseudo-bands describing textural or geometrical
characteristics, and then run the process I described above.


2017-03-02 15:41 GMT+01:00 <[email protected]>:

> Shouldn't we use spectral, spatial, and contextual attributes of our
> objects (segments) while we are classifying our image? Isn't this the
> difference between the object-based and pixel-based classifications?
>
> I'm not sure if I'm on the right track or not but I thought I should
> calculate the spectral, spatial, and contextual attributes of the objects
> both in segmented image and training vector file and by the algorithms like
> RandomForest find the resemblance and finally generate the classified map.
>
> On Thursday, March 2, 2017 at 5:06:01 AM UTC-3:30, Arnaud Durand wrote:
>>
>> The application ObjectsRadiometricStatistics only put shape and
>> radiometric information in the attribute table of a Shapefile representing
>> a segmentation.
>> The idea is to permit in a further step a selection by attributes with a
>> GIS software.
>>
>> --
> --
> Check the OTB FAQ at
> http://www.orfeo-toolbox.org/FAQ.html
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