(Also cross-referenced as CAR-TR-693)

A probe based approach is used to recognize objects in a cluttered

background using an infrared imager. A probe is a simple mathematical function which operates locally on image grey levels and produces an output that is more directly usable by an algori thm. A directional probe image is calculated by taking the difference in grey levels between pixels a set distance apart in a given direction, centered on the probe image pixel. These probe images contain the information necessary for use by an object rec ognition algorithm in a readily usable, and mathematically describable, form. A parametric statistical image background model which describes the probe images is introduced. The parameters of the probe image model can be readily estimated from the image. Knowledge of these parameters, together with target signatures obtained from Computer Aided Design (CAD) models, allows the likelihood ratio for a given object pose hypothesis versus the background null hypothesis to be written. The generalized likelihood ratio test is used to accept one of the object poses or to choose the null hypothesis. Results of the method applied to a large set of terrain model board images are presented.