The Two-Point Correlation Function: A Measure of Interclass Separability

Authors:
N. Fatemi-Ghomi;P. L. Palmer;M. Petrou
Affiliations:
Department of Electronics and Electrical Engineering, University of Surrey, Guildford GU2 5XH;Department of Electronics and Electrical Engineering, University of Surrey, Guildford GU2 5XH;Department of Electronics and Electrical Engineering, University of Surrey, Guildford GU2 5XH
Venue:
Journal of Mathematical Imaging and Vision
Year:
1999

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Abstract

In this paper we introduce the two-point correlation function as ameasure of interclass separability. We present a theoretical study ofthis statistic in a general M-dimensional feature space and propose afast algorithm for the efficient computation of it. We test thealgorithm and illustrate the properties of the statistic using test datain 1D and 2D feature spaces and discuss the boundary effects of thefeature space. We also present a discussion of the limitations of theproposed statistic and apply it to the assessment of inter-classseparability in a texture segmentation context.