Texture Analysis by Accurate Identification of Simple Markovian Models

A more accurate identification (estimation of parameters) of simple Markov-Gibbs random field models of images results in a better segmentation of specific multimodal images and realistic synthesis of some types of natural textures. Identification algorithms for segmentation are based in part on a novel modification of an unsupervised learning algorithm published first in “Cybernetics and Systems Analysis” (“Kibernetika i Sistemnyi Analiz”) almost four decades ago. A texture synthesis algorithm uses an identified model for selecting a characteristic geometric shape of and a placement grid for texture elements sampled from a training image utilized for the identification.

[1]  David G. Stork,et al.  Pattern Classification , 1973 .

[2]  Aly A. Farag,et al.  Iterative Approximation of Empirical Grey-Level Distributions for Precise Segmentation of Multimodal Images , 2005, EURASIP J. Adv. Signal Process..

[3]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

[4]  Herbert Süße,et al.  Invariant Fitting of Planar Objects by Primitives , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Dongxiao Zhou.  Model-based Estimation of Texels and Placement Grids for Fast Realistic Texture Synthesis , 2003 .

[6]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Phil Brodatz,et al.  Textures: A Photographic Album for Artists and Designers , 1966 .

[8]  A. Farag,et al.  Expectation-maximization for a linear combination of Gaussians , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[9]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[10]  Sung Yong Shin,et al.  On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..

[11]  A. Ardeshir Goshtasby,et al.  Curve Fitting by a Sum of Gaussians , 1994, CVGIP Graph. Model. Image Process..

[12]  M. Hassner,et al.  The Use of Markov Random Fields as Models of Texture , 1981 .

[13]  Baining Guo,et al.  Real-time texture synthesis by patch-based sampling , 2001, TOGS.

[14]  Anuj Srivastava,et al.  Universal Analytical Forms for Modeling Image Probabilities , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  H. Sorenson,et al.  Recursive bayesian estimation using gaussian sums , 1971 .

[16]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[17]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[18]  B. Julesz.  Textons, the elements of texture perception, and their interactions , 1981, Nature.

[19]  J. F. C. Kingman,et al.  Information and Exponential Families in Statistical Theory , 1980 .

[20]  Alexei A. Efros,et al.  Image quilting for texture synthesis and transfer , 2001, SIGGRAPH.

[21]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[22]  G. Gimel'farb.  A general approach to the construction of statistically optimal algorithms for pattern recognition , 1967 .

[23]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[24]  Georgy L. Gimel'farb,et al.  Image Textures and Gibbs Random Fields , 1999, Computational Imaging and Vision.

[25]  Georgy L. Gimel'farb,et al.  Texture Modelling by Multiple Pairwise Pixel , 2008 .

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

[27]  Anil K. Jain,et al.  Markov Random Field Texture Models , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Václav Hlavác,et al.  Ten Lectures on Statistical and Structural Pattern Recognition , 2002, Computational Imaging and Vision.

[29]  Aly A. Farag,et al.  Expectation-maximization for a linear combination of Gaussians , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[30]  Irfan A. Essa,et al.  Graphcut textures: image and video synthesis using graph cuts , 2003, ACM Trans. Graph..

[31]  Anil K. Jain,et al.  Random field models in image analysis , 1989 .

[32]  Luc Van Gool,et al.  Cut-primed smart copying , 2003 .