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A Fast Texture Classifier Based on Cross Entropy Minimisation

M. Unser

Proceedings of the Second European Signal Processing Conference on Theories and Applications (EUSIPCO'83), Erlangen, Federal Republic of Germany, September 12-16, 1983, pp. 261-264.

A fast texture classification algorithm based on measurements of the spatial grey level co-occurrence matrix is presented. Classification is performed by comparing computed minimum cross entropies under constraints (measurements) with respect to some reference statistics. The originality of this approach, besides its information theoretic formulation, relies on the fact that optimum classification is performed without an explicit estimation of the measurement vectors (spatial grey level co-occurrence matrix). As a complement the specific problem of conformity testing (one class classification problem) is also investigated.

AUTHOR="Unser, M.",
TITLE="A Fast Texture Classifier Based on Cross Entropy
BOOKTITLE="Proceedings of the Second European Signal Processing
        Conference on Theories and Applications ({EUSIPCO'83})",
address="Erlangen, Federal Republic of Germany",
month="September 12-16,",

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