I am making a preliminary selection of algorithms to use for
recognizing a collection of objects in images. I have a simulation
that creates a set of objects all the combinations of range and size
differences. I want to run a collection of algorithms that calculate
"moments" of an image on each, to determine between what types of
objects (e.g., collections of different shapes) a particular
algorithm can differentiate.

Since I am simulating discrete amounts of range and size and not
yet dealing with random variables, I will get a fixed value for the
moment calculations for each one. There is no random variance in
this data set. (Later I will test with some other, random variables
in the
data.)

My question is: Can I validly use an ANOVA and/or cluster analysis
on this data set (with no random variables), to see between which
groups of shapes --- varying only non-random variables --- the
algorithms can
differentiate over the range of factors I am varying?

I think I can validly do this. What is your thought on this?

Thanks, Alan