Hypothesizing and testing geometric attributes of image data

A general formalism for detecting geometric configurations of image data is presented. The author first estimates an ideal geometric configuration that supposedly exists, and then checks to what extent the original edges must be displaced in order to support the hypothesis. All types of tests are reduced to computing a single measure of edge displacement which provides a universal measure of uncertainty applicable to all types of decision-making.<<ETX>>