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Decorrelation Methods of Texture Feature Extraction
April 1980 (vol. 2 no. 4)
pp. 323-332
Olivier D. Faugeras, MEMBER, IEEE, Institut de Recherche d'Informatique et d'Automatique, Domaine de Voluceau, Rocquencourt, Le Chesnay, France; Department of Electrical Engineering, University of Sout
William K. Pratt, SENIOR MEMBER, IEEE, Image Processing Institute, University of Southern California, Los Angeles, CA 90007; Compression Labs., Inc., Cupertino, CA 95014.
This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination. A texture feature extraction technique involving autocorrelation function measurement of a texture field, combined with histogram representation of a statistically decorrelated version of the texture field, is introduced. The texture feature extraction method is evaluated in terms of a Bhattacharyya distance measure.
Citation:
Olivier D. Faugeras, William K. Pratt, "Decorrelation Methods of Texture Feature Extraction," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 4, pp. 323-332, April 1980, doi:10.1109/TPAMI.1980.4767031
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