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