Share Email Print
cover

Proceedings Paper

Shape Matching Of Two-Dimensional Occluded Objects
Author(s): Yu-Shan Fong; Jwo-Liang Chu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Recognition of partially occluded object is a desirable function in a computer vision system, especially one employed in an industrial automation environment. In this controlled environment, the objects to be recognized can be constrained to a relatively flat region (plane of image), and thus be easily modelled by polygons. This paper studies issues in such a computer vision system and presents algorithms for the various processes involved in occluded polygon matching and recognition. The recognition process is carried out by model matching. The scene may contain unknown model objects which may overlap or touch each other, giving rise to partial occlusion. Both the model and the scene objects are represented by their polygon approximations. Features used for matching are extracted from line segments connecting all possible pairs of vertices in the polygon. They are: vertex types at two ends of line segment, angles of these vertices, line type, and line length. A polygon clipping algorithm based on geometrical properties is used to determine the types of line segments. We also develop a context-free grammar for recognizing line types. To speed up the recognition process, only priority features are used in the initial matching. The priority features are identified after some analysis of the geometrical properties of polygons with occlusion. A consistency check also reduces the pool of candidates for matching. The matching algorithm superposes the model object on the scene along line segments in sequence and checks the dissimilarity between the region enclosed by the scene polygon and the region enclosed by the model polygon appearing in the scene. A dissimilarity measure based on the phenomenon of light illumination and the theory of fuzzy subset has been designed to measure the edge consistency between the scene and candidate model to select the best possible fit.

Paper Details

Date Published: 13 October 1987
PDF: 11 pages
Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); doi: 10.1117/12.976489
Show Author Affiliations
Yu-Shan Fong, Clarkson University (United States)
Jwo-Liang Chu, Clarkson University (United States)


Published in SPIE Proceedings Vol. 0845:
Visual Communications and Image Processing II
T. Russell Hsing, Editor(s)

© SPIE. Terms of Use
Back to Top