Intra-class variability in ATR systems

In this paper we describe the results of our investigation into the intra-class variability of a vehicle class (T-72 Tanks) from the perspective of an Automatic Target Recognition system. We examine the performance of synthesized vehicle models for ATR systems and demonstrate that these models fall within the bounds of the vehicle class set by the intra-class variability of the vehicle. We then demonstrate the relevance of the mean-square-error between an image chip and a template as a useful measure of distance between the two vehicles. We also show that it is possible to constitute a superior class representative and classifier by combining chips from two different vehicles while constructing the templates.