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An Empirical Evaluation of Generalized Cooccurrence Matrices
February 1981 (vol. 3 no. 2)
pp. 214-221
L. S. Davis, Department of Computer Sciences, University of Texas at Austin, Austin, TX 78712.
M. Clearman, Department of Computer Sciences, University of Texas at Austin, Austin, TX 78712.
J. K. Aggarwal, Department of Electrical Engineering, University of Texas at Austin, Austin, TX 78712.
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.
Citation:
L. S. Davis, M. Clearman, J. K. Aggarwal, "An Empirical Evaluation of Generalized Cooccurrence Matrices," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 2, pp. 214-221, Feb. 1981, doi:10.1109/TPAMI.1981.4767084
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