An Empirical Evaluation of Generalized Cooccurrence Matrices

Authors:
L. S. Davis;M. Clearman;J. K. Aggarwal
Affiliations:
Department of Computer Sciences, University of Texas at Austin, Austin, TX 78712.;Department of Computer Sciences, University of Texas at Austin, Austin, TX 78712.;Department of Electrical Engineering, University of Texas at Austin, Austin, TX 78712.
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1981

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Abstract

A comparative study of generalized cooccurrence texture analysis tools is presented. A generalized cooccurrence matrix (GCM) reflects the shape, size, and spatial arrangement of texture features. The particular texture features considered in this paper are 1) pixel-intensity, for which generalized cooccurrence reduces to traditional cooccurrence; 2) edge-pixel; and 3) extended-edges. Three experiments are discussed-the first based on a nearest neighbor classifier, the second on a linear discriminant classifier, and the third on the Battacharyya distance figure of merit.