Decorrelation Methods of Texture Feature Extraction

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.

[1]  Béla Julesz,et al.  Visual Pattern Discrimination , 1962, IRE Trans. Inf. Theory.

[2]  J. Pokorny Foundations of Cyclopean Perception , 1972 .

[3]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[4]  I. Pollack Discrimination of third-order Markov constraints within visual displays , 1973 .

[5]  B Julesz,et al.  Inability of Humans to Discriminate between Visual Textures That Agree in Second-Order Statistics—Revisited , 1973, Perception.

[6]  R. Haralick,et al.  Computer Classification of Reservoir Sandstones , 1973 .

[7]  B Julesz,et al.  Experiments in the visual perception of texture. , 1975, Scientific American.

[8]  Azriel Rosenfeld,et al.  A Comparative Study of Texture Measures for Terrain Classification , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  W. Richards,et al.  Visual texture discrimination using random-dot patterns. , 1977, Journal of the Optical Society of America.

[10]  Olivier D. Faugeras,et al.  Visual Discrimination of Stochastic Texture Fields , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  R.M. Haralick,et al.  Statistical and structural approaches to texture , 1979, Proceedings of the IEEE.