رکورد قبلیرکورد بعدی

" Image Textures and Gibbs Random Fields "


Document Type : BL
Record Number : 728681
Doc. No : b548433
Main Entry : by Georgy L. Gimel'farb.
Title & Author : Image Textures and Gibbs Random Fields\ by Georgy L. Gimel'farb.
Publication Statement : Dordrecht: Springer Netherlands, 1999
Series Statement : Computational imaging and vision, 16.
Page. NO : (xiv, 251 pages)
ISBN : 9401144613
: : 9789401144612
Contents : Instead of introduction --;1 Texture, Structure, and Pairwise Interactions --;1.1 Human and computational views --;1.2 Spatial homogeneity, or self-similarity of textures --;1.3 Basic notation and notions --;1.4 Random fields and probabilistic image modelling --;1.5 Physics and image modelling: what an interaction means --;1.6 GPDs and exponential families of distributions --;1.7 Stochastic relaxation and stochastic approximation --;2 Markov and Non-Markov Gibbs Image Models --;2.1 Traditional Markov/Gibbs image models --;2.2 Generalized Gibbs models of homogeneous textures --;2.3 Prior Markov/Gibbs models of region maps --;2.4 Piecewise-homogeneous textures --;2.5 Basic features of the models --;3 Supervised MLE-Based Parameter Learning --;3.1 Affine independence of sample histograms --;3.2 MLE of Gibbs potentials --;3.3 Analytic first approximation of potentials --;3.4 Most characteristic interaction structure --;3.5 Stochastic approximation to refine potentials --;4 Supervised Conditional MLE-Based Learning --;4.1 The least upper bound condition --;4.2 Potentials in analytic form --;4.3 Practical consistency of the MLEs --;5 Experiments in Simulating Natural Textures --;5.1 Comparison of natural and simulated textures --;5.2 "Brodatz" image database --;5.3 Interaction maps and texture features --;5.4 CSA vs. traditional modelling scenario --;5.5 "MIT VisTex" image database --;6 Experiments in Retrieving Natural Textures --;6.1 Query-by-image texture retrieval --;6.2 Similarity under scale and orientation variations --;6.3 Matching two textures --;6.4 Experiments with natural textures --;6.5 Complexity and practicality --;7 Experiments in Segmenting Natural Textures --;7.1 Initial and final segmentation --;7.2 Artificial collages of Brodatz textures --;7.3 Natural piecewise-homogeneous images --;7.4 How to choose an interaction structure --;7.5 Do Gibbs models learn what we expect? --;Texture Modelling: Theory vs. Heuristics --;References.
Abstract : Image analysis is one of the most challenging areas in today's computer sci- ence, and image technologies are used in a host of applications.
Subject : Artificial intelligence.
Subject : Computer science.
Subject : Data structures (Computer science)
Added Entry : Georgy L Gimel'farb
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