Authors:
Tyler Laforet
and
Pascal Matsakis
Affiliation:
School of Computer Science, University of Guelph, Stone Rd E, Guelph, Canada
Keyword(s):
Image Descriptors, Relative Position Descriptors, φ-Descriptor, Spatial Relationships, Vector Objects, 2-Dimensional.
Abstract:
In regular conversation, one often refers to the spatial relationships between objects via their positions relative to each other. Relative Position Descriptors (RPDs) are a type of image descriptor tuned to extract these spatial relationships from pairs of objects. Of the existing RPDs, the φ-descriptor covers the widest variety of spatial relationships. Currently, algorithms exist for its computation in the case of both 2D raster and vector objects. However, the algorithm for 2D vector calculation can only handle pairs of simple polygons and lacks some key features, including support for objects with disjoint parts/holes, shared polygon vertices/edges, and various spatial relationships. This paper presents an approach for complex polygonal object φ-descriptor computation, built upon the previous. The new algorithm utilizes the analysis of object boundaries, polygon edges that represent changes in spatial relationships, and brings it more in-line with the 2D raster approach.