Unsupervised texture segmentation using feature distributions

Abstract This paper presents an unsupervised texture segmentation method, which uses distributions of local binary patterns and pattern contrasts for measuring the similarity of adjacent image regions during the segmentation process. Nonparametric log-likelihood test, the G statistic, is engaged as a pseudo-metric for comparing feature distributions. A region-based algorithm is developed for coarse image segmentation and a pixelwise classification scheme for improving localization of region boundaries. The performance of the method is evaluated with various types of test images.

[1]  Anil K. Jain,et al.  Texture Analysis , 2018, Handbook of Image Processing and Computer Vision.

[2]  Michael Spann,et al.  A quad-tree approach to image segmentation which combines statistical and spatial information , 1985, Pattern Recognit..

[3]  Larry S. Davis,et al.  MITES (mit-æs): A model-driven, iterative texture segmentation algorithm , 1982, Comput. Graph. Image Process..

[4]  David B. Cooper,et al.  Bayesian Clustering for Unsupervised Estimation of Surface and Texture Models , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[6]  Rama Chellappa,et al.  Learning Texture Discrimination Rules in a Multiresolution System , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Matti Pietikäinen,et al.  Accurate color discrimination with classification based on feature distributions , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[8]  Jian Fan,et al.  Frame representations for texture segmentation , 1996, IEEE Trans. Image Process..

[9]  Rama Chellappa,et al.  Unsupervised Texture Segmentation Using Markov Random Field Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Matti Pietikäinen,et al.  Determining Composition of Grain Mixtures by Texture Classification Based on Feature Distributions , 1996, Int. J. Pattern Recognit. Artif. Intell..

[11]  Wilson S. Geisler,et al.  Multichannel Texture Analysis Using Localized Spatial Filters , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Anil K. Jain,et al.  Learning Texture Discrimination Masks , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Linda G. Shapiro,et al.  Image Segmentation Techniques , 1984, Other Conferences.

[14]  Anil K. Jain,et al.  Texture classification and segmentation using multiresolution simultaneous autoregressive models , 1992, Pattern Recognit..

[15]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[16]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[17]  Patrick C. Chen,et al.  Segmentation by texture using a co-occurrence matrix and a split-and-merge algorithm☆ , 1979 .

[18]  R. Sokal,et al.  Introduction to biostatistics , 1974 .

[19]  Glenn Healey,et al.  Markov Random Field Models for Unsupervised Segmentation of Textured Color Images , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Richard C. Dubes,et al.  Performance evaluation for four classes of textural features , 1992, Pattern Recognit..

[21]  Jia-Lin Chen,et al.  Unsupervised texture segmentation using multichannel decomposition and hidden Markov models , 1995, IEEE Trans. Image Process..

[22]  J. M. Hans du Buf,et al.  A review of recent texture segmentation and feature extraction techniques , 1993 .

[23]  Matti Pietikäinen,et al.  Texture classification by center-symmetric auto-correlation, using Kullback discrimination of distributions , 1995, Pattern Recognit. Lett..

[24]  Bidyut Baran Chaudhuri,et al.  Texture Segmentation Using Fractal Dimension , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  A. Khotanzad,et al.  A Parallel, Non-parametric, Non-iteratrve Clustering Algorithm With Application To Image Segmentation , 1988, Twenty-Second Asilomar Conference on Signals, Systems and Computers.

[26]  Zhigang Fan,et al.  Maximum likelihood unsupervised textured image segmentation , 1992, CVGIP Graph. Model. Image Process..

[27]  Michael Unser,et al.  Multiresolution Feature Extraction and Selection for Texture Segmentation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Alexander A. Sawchuk,et al.  Supervised Textured Image Segmentation Using Feature Smoothing and Probabilistic Relaxation Techniques , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

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

[30]  Alexander A. Sawchuk,et al.  Unsupervised textured image segmentation using feature smoothing and probabilistic relaxation techniques , 1989, Comput. Vis. Graph. Image Process..

[31]  Charles A. Bouman,et al.  Multiple Resolution Segmentation of Textured Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Ajai Jain,et al.  The Handbook of Pattern Recognition and Computer Vision , 1993 .

[33]  A. Rosenfeld,et al.  Image Segmentation by Texture Using Pyramid Node Linking. , 1981 .

[34]  Michael Unser,et al.  Texture classification and segmentation using wavelet frames , 1995, IEEE Trans. Image Process..