<title>Relational graph representation of color images for model-based matching using relational distance measurement</title>

Abstract

In this paper we present the relational graph description of natural color scenes for model- based matching using relational distance measurement. The uniformly colored object areas and the textured surfaces of natural scenes are extracted using color clustering and linear discriminant. The extracted object regions are refined in the spatial plane to eliminate the fine grain segmentation results. The refined segments are then represented using an adjacency relation graph. Scene model is formed by means of 3D to 2D constraints and adjacency relations. The relational-distance measure is used for matching the relational graphs of the input scene and the respective image. Experiments are conducted on imperfect color images of outdoor scenes involving complex shaped objects and irregular textures. The algorithm has produced relatively simple relational graph representation of the input scenes and accurate relational-distance-based matching results.