Annular symmetry operators: a method for locating and describing objects

We present a machine vision system in which segmentation is computed in conjunction with a structural description of objects in the scene. It is assumed that contrast edges capture all relevant object information. The principles which dictate how edge features are grouped to infer objects are based upon detecting SYMMETRICAL ENCLOSING edge configurations. These are detected using ANNULAR OPERATORS applied at multiple scales to edge data which have been extracted at multiple scales from a gray level image. The subsequent grouping of symmetry points results in a set of PARTS which make it possible to identify the LOCATION of objects within an image. These parts are used as a basis for constructing coarse graph-based DESCRIPTORS for the PERCEPTUALLY SIGNIFICANT objects found in the scene. Results are presented to illustrate the method´s performance on several images