Model Generation And Inexact Matching For Object Identification

Chung Lin Huang

doi:10.1117/12.970174

1 November 1989 Model Generation And Inexact Matching For Object Identification

Chung Lin Huang

Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970174
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

In this paper we present a hierarchical inexact matching method to identify 3-D objects. The 3-D objects are described by a relational model consisting of the global relation, the topological relation, and the geometrical relation. When identifying an unknown object, firstly its global, topological, and geometrical relations are generated, secondly its global relation is used as a key to search for the closest group of clusters, thirdly its topological relation is matched with the representative of each cluster in the same group to find the most similar cluster, and finally the geometrical relation match takes place against the objects in this cluster for the best match. The hierarchical relational model generation and inexact matching are both simple and powerful. The matching procedure incorporating weights, thresholds, and constraint relations is highly flexible.

Citation Download Citation

Chung Lin Huang "Model Generation And Inexact Matching For Object Identification", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970174

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available