High resolution electro-optical sensors are emerging from technology, offering a capability to remotely determine geometric shape of objects. In terms of military reconnaissance and surveilance needs, this capability enhances the potential to detect, classify, and identify enemy targets automatically, and record or report only their type and location. The objective of this paper is to outline the general nature of an automatic classifier for processing high resolution, active electro-optical sensor data on the basis of target dimensional features. A simple geometric analysis is used to demonstrate the predominant features of the data, and to suggest approaches for cueing potential targets by masking out extraneous background data. The goal is to provide an early data reduction so that potential target subframes can be processed in the classification processor at lower data rates. Both line-scan and raster-scan data formats are considered, in forward- and down-looking configurations.