Hierarchical maximum entropy partitioning in texture image analysis

Abstract This paper presents an effective texture representation which captures the statistics (or distributions) of structural and/or spatial relations of grey levels within certain neighborhood in a texture image. The structural and/or spatial relations are captured by various feature extraction operators to generate feature images. Then, the joint distributions of the features which we termed feature frequency matrices (FFM) provide the statistics and representation of the texture image. A partitioning scheme to ‘compress’ the FFM such that only relevant information is retained is proposed. The partitioning scheme is based on the hierarchical maximum entropy discretization scheme which minimizes the loss of information. The efficacy of the representation is demonstrated using homogeneous texture images.

[1]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[2]  Robert King,et al.  Textural features corresponding to textural properties , 1989, IEEE Trans. Syst. Man Cybern..

[3]  Rama Chellappa,et al.  Texture classification using features derived from random field models , 1982, Pattern Recognit. Lett..

[4]  Harry Wechsler,et al.  Texture analysis — a survey , 1980 .

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

[6]  Helen C. Shen,et al.  Generalized texture representation and metric , 1983, Comput. Vis. Graph. Image Process..

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

[8]  J. G. Kalbfleisch.  Probability and Statistical Inference , 1977 .

[9]  Anil K. Jain,et al.  A spatial filtering approach to texture analysis , 1985, Pattern Recognit. Lett..

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

[11]  Andrew K. C. Wong,et al.  Information synthesis based on hierarchical maximum entropy discretization , 1990, J. Exp. Theor. Artif. Intell..

[12]  Luc Van Gool,et al.  Texture analysis Anno 1983 , 1985, Comput. Vis. Graph. Image Process..

[13]  Azriel Rosenfeld,et al.  Experiments with texture classification using averages of local pattern matches , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  Andrew K. C. Wong,et al.  Information Discovery through Hierarchical Maximum Entropy Discretization and Synthesis , 1991, Knowledge Discovery in Databases.

[15]  Helen C. Shen,et al.  Feature frequency matrices as texture image representation , 1992, Pattern Recognit. Lett..

[16]  Random field identification from a sample: Experimental results , 1988, Pattern Recognit. Lett..