Edge Detection does not help clustering

It appears that all the SOM weights fed by edge-detection are very similar:

codebooks.png

Corresponding to these resulting accumulations:

table2-subset-try1-montage.jpg

I think the poor accumulations are due to poor distance measures considering the edge-detections. The next step is to break the objects into a few Euclidean blocks, and calculate hists from those blocks. They should be much more flexible regarding object edges than the edge-detection. Basically it appears that two edge-detections of the same object in different orientations are as different as edge-detections of two different objects.