Object identification and retrieval in a CAST library

  • Charles Rattray
  • Marion Marsden
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 585)

Abstract

The classification and recognition problems are fundamental to an understanding of object identification and retrieval in a CAST library or repository.

In this paper, we have attempted to provide a framework in the guise of categories of approximations and categorical shape theory, in which to consider these problems. In doing so, we have chosen to specify CAST objects in terms of well-defined mathematical entities, namely, sketches. Crucial to classification and recognition in this context is the need to match sketches. By emphasising their geometric aspects we have suggested that a graph theoretic view of matching might be fruitful.

Much more work needs to be done, of course, to exploit categorical shape theory and the theory of sketches in this area. The geometric matching algorithm, too, must be generalised to deal properly with cones and cocones, and to deal with partial matching of sketches. This is not trivial and may benefit from the generalised matching algorithm design approach of Srinivas, based on sheaf theory [32].

Keywords

Equivalence Class Object Identification System Requirement Graph Theoretic Approach Derivational Analogy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Charles Rattray
    • 1
  • Marion Marsden
    • 1
  1. 1.Department of Computing ScienceUniversity of StirlingStirlingScotland

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