I am trying to run an object-based classification using Orfeo and R. The 
Landsat images were segmented using Monteverdi (Orfeo Toolbox).
My problem is that the results (confusion matrix) are represented as the 
total number of pixels per class instead of number of segments as training 
object. 
I applied the following steps: 
   
   1. The landsat images were segmented using the 4 steps of Large Scale 
   Mean Shift Segmentation LSMS (Orfeo Toolbox). The segments generated in the 
   4th step of LSMS is a shapefile.
   2. Training samples (segments) were selected from the LSMS 4.
   3. Then I applied the classification using the original Landsat Image as 
   input image.

The classification doesn't allocate the whole segments per class, rather it 
allocate number of pixels within a segment. Although I segmented the images 
using the LSMS approach, the Landsat image are not considered an object in 
the classification. For that reason my results are basically an pixel based 
classification instead of object-based.

It seems that I am missing a step in order to have an object based 
classification. 
I really appreciate any help.

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