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Issue No.02 - February (1981 vol.3)
pp: 214-221
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.
M. Clearman, J. K. Aggarwal, "An Empirical Evaluation of Generalized Cooccurrence Matrices", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.3, no. 2, pp. 214-221, February 1981, doi:10.1109/TPAMI.1981.4767084
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