Fuzzy relaxation approach for inexact scene matching

Abstract

A graph theoretic approach for matching imperfectly segmented images with stored scene models is presented. The segmentation errors addressed are missing objects, extra objects, mismeasured relations, mismeasured attributes, split objects, and merged objects. By combining enhanced fuzzy relaxation and association graph techniques, the mthod integrates global inter-object relations and local object attributes to obtain more reliable matching. Problems of oversegmentation and undersegmentation are handled by modifying the association graph to include nodes involving merged regions and objects.