A Mathematical Model For Representing Patterns And Pattern Classes Using Semantic Nets

A. M. Gokeri

doi:10.1117/12.946181

17 January 1985 A Mathematical Model For Representing Patterns And Pattern Classes Using Semantic Nets

A. M. Gokeri

Proceedings Volume 0521, Intelligent Robots and Computer Vision; (1985) https://doi.org/10.1117/12.946181
Event: 1984 Cambridge Symposium, 1984, Cambridge, United States

Abstract

A set theoratical model for representing pattern and pattern classes was previously proposed (Gokeri, 1983). In this paper a method for matching the semantic net model of a given pattern with the elements of a set of pattern class models is proposed. Accordingly, for a pattern class a new mathematical model, M, is defined such that M=<P,ψ>, P is a semantic net defining the pattern class and ψ:PxP →[0,1] is a probability function. ψ(fi,fj) may be interpreted as the conditional probability of occurrence of feature Fi with given Fj. Using these values and an empirically developed decision function, Δ , a .1 measure of simiiarity between the model of a pattern class and model of a sample pattern is determined. The Δ- function returns a scalar value in the interval [-1, 1] such that positive values signify similarity. If A=0, no decision can be made regarding the degree of semblance between two semantic net models, and negative values of A indicate no likeness. Finally, a method for modifying the decision function is offered.

Citation Download Citation

A. M. Gokeri "A Mathematical Model For Representing Patterns And Pattern Classes Using Semantic Nets", Proc. SPIE 0521, Intelligent Robots and Computer Vision, (17 January 1985); https://doi.org/10.1117/12.946181

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