Kopparapu S.K., Desai U.D. — Bayesian Approach to Image Interpretation :: Электронная библиотека попечительского совета мехмата МГУ

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Kopparapu S.K., Desai U.D. — Bayesian Approach to Image Interpretation

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Название: Bayesian Approach to Image Interpretation

Авторы: Kopparapu S.K., Desai U.D.

Аннотация:

Writing for students and researchers in the field, Kopparapu (research and development for a private company in Bangalore, India) and Desai (electrical engineering, Indian Institute of Technology, Bombay) present a description and up-to-date treatment of image interpretation. The initial chapters describe the state of research, Markov random fields, their application to computer vision, the concept of cliques, and Bayesian network image interpretation. The authors then propose a new approach that applies synergism between the process of segmentation and interpretation in a multi-resolution framework and presents a joint segmentation and image interpretation algorithm.

Язык:

Рубрика: Computer science/Обработка изображений/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2002

Количество страниц: 127

Добавлена в каталог: 19.11.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

Adjacency constraints      7
Adjacency graph      37 43 53
Adjacent regions      114
Admissibility criterion      29—30
Algebraic topology      6
Algorithm, joint segmentation and image interpretation      64
Algorithm, k-means      99
Algorithm, segmentation      107
Algorithm, segmentations      62
Algorithm, simulated annealing      91
Analytic function      84
Annealing schedule      9
Anti-sampling      95
Automatic target recognition      79
Bandpass filter      24
Basis function      8 41 76
Basis function, linear      76
Bayes rule      19
Bayes theorem      19 45
Bayesian approach      13
Bayesian network      10 8 43—55 97
Bayesian network, singly-connected      50—51
Bayesian network, updating      49
Bayesian networks      5—6 43—44 47 51
Bayesian networks, properties      48
Bayesian Reconstruction      81
Beliefnetworks      8
Biomedical science      5
Blurring matrix      19
Boltzmann machine      12
Causal network      47
Causal networks      8
Cellular automata      6
Centre frequency      24
Centroid      113
Centroids      99
CLIQUE      1—17 36 38 44 84 87—88 114
Clique function      10 37 39 41 64
Clique parameters      35
Clique potential      8 37
Clique potentials      67
Clique, 1-node      39 41
Clique, 2-node      37 41
Clique, 3-node      37
Clique, functions      35 38 42 55
Clique, multiple node      39
Clique, n-node      114
Cliques      8 23 37 44 50 52—53 86
Cliques functions      80
Coarse to fine      33
Color editor      108
Combinatorial      42
Combinatorics      12
Compactness      4.37 110
Conditional distribution      48 55
Conditional distributions      55
Conditional pdf      55
conditional probabilities      48 50 54 76
Conditional probability      8—9 14 20—21 24 63 67 81
Conditionally independent      53
Convolve      28
Cooling schedule      24 91
Cost function      12 99
Custom made pyramids      26
D-separated      49 53
D-Separation      49
Data perturbation      113
Data structure.      24
Data structures      95
Daubechies filter      69
Degradation model      81 92
Dempster — Shafer theory      9
Densitometric      6
Density functions      76
Depth estimation      2
Detection      11
Difference image      63
Dilation parameter      29
Directed acyclic graph      47
Discontinuities      81
Discrete wavelet transform      30
Distortion threshold      99
Domain independent      6
Domain knowledge      4—5 7—8 35 37—40 41 43—45 55 63—64
Down sample      28
Down-sampled      28
Dyadic wavelet      30
Earlyvision      11 19 22
Edge detection      2 11
Edge fields      66
Energy function      9 13 16—17 20 63—64 78
Energy minimization      12
Equal contribution      27
Evidential reasoning      50
Expert system      7
Expert Systems      44 46
Feature selection      101
Feature vector      113
Feature, area      101 103
Feature, aspect ratio      103
Feature, boundarylength      103
Feature, common perimeter      102
Feature, compactness      102
Feature, contrast      103
Feature, convex area      103
Feature, convexity      104
Feature, curl      104
Feature, elongation      104
Feature, extent      104
Feature, gray value      102
Feature, mass center      102
Feature, maximum diameter      101
Feature, minimum diameter      101
Feature, orientation      102
Feature, perimeter      101
Feature, roundness      103
Feature, scatter matrix      102
Feature, solidity      104
Feature, variance      102
features      4 110
Feedback process      6
Ferro magnetism      17
Finite configuration      83
Form factor      110
Fourier transform      29
Fovea      32
Fuzzy expert system      7
Fuzzy set      8
Fuzzy systems      40
Ganglion cells      33
Gaussian      81
Gaussian distribution      19
Gaussian pyramid      26 29
General purpose computers      1
Genetic algorithm      42
Gibbs distributed      36
Gibbs distribution      13
Gibbs energy      36
Gibbs sampling      44 51
Gibbsian distribution      19
Gibbsianpdf      51 53
Gradient decent      91
Graph      47
Hammersley — Clifford theorem      90
Hierarchical decision      7
High level vision      79
High pass filter      26 31 62
High-level vision      2 11 74
histogram      5 55 100
HMM      113

Hopfield network      13
Horizontal edge      22
Human visual cortex      26
Human visual system      1 3
HVS      1 25
I.i.d.      19
Ill-posed      11
Image discontinuities      12
Image interpretation      3 8 35 37—38 43—44 53 59—61 63—64 69 74 76 78 80 101 107
Image recognition      2
Image reconstruction      81
Image restoration      13 22 81 92
Image-image task      2
Image-scene task      2
Imaging device      82
Independence networks      8
Inner product      29
Interpolate      68
Interpret      2
Interpretation      5 9 37 42 46 73 80
Interpretation block      6 69
Interpretation labels      5 64 69
Interpretation module      60 62 69 71
Interpretation network      52
Interpretation scheme      78
Interpretation, aerial images      5
Interpretation, approaches      7
Interpretation, astronomical images      5
Interpretation, Bayesian network      5
Interpretation, biomedical      5
Interpretation, block, knowledge acquisition      5
Interpretation, cellular automata      6
Interpretation, color images      5
Interpretation, deformable template      6
Interpretation, Fourier domain      6
Interpretation, genetic algorithm      6
Interpretation, geophysical images      5
Interpretation, infra red images      5
Interpretation, knowledge based      6
Interpretation, laser radar images      5
Interpretation, literature      5
Interpretation, Markov random field      6 8
Interpretation, natural scene      5
Interpretation, neural networks      8
Interpretation, probabilistic approach      7
Interpretation, projective invariants      6
Interpretation, range image      5
Interpretation, remote sense images      5
Interpretation, rules for      7
Interpretation, SAR images      5
Interpretation, satellite images      5
Interpretation, scheme      4
Interpretation, seismic images      5
Interpretation, thermal images      5
Interpretation, three blocks      5
Interpretation, two block      4
Interpretation, ultra sound images      5
Interpretations      44—45
Inverse exponential      81
Inverse optics      11
Ising model      17
Isolated features      5 7
Joint density function      47
Joint distribution      48—49 51
Joint HMM      114
Joint pdf.      51 54
Joint probability distribution      48 51—52
Joint segmentation and integration      62
K-means      75 107
K-means clustering      9 62 64—65 67 69 99 107
K-means segmentation      72 107
K-means segmented      107
Knowledge acquisition      5 107
Knowledge aquization      69
Knowledge base      67—68 71 73 76
Knowledge pyramid      68
Knowledge-based      43
Label      66
Label, no-interpretation      63.67
Labelled image      108
Labelling      2 37 44 107
Labelling algorithm      107
labels      44 60 67 71 75
Lagrange multipliers      18
Laplacian pyramid      26
Lattice      14 22 26
lexicographical ordering      13 18 21
Line field      22
Linear basis function      76
Local maxima      100
Locality property      14 19 21
Low pass filter      26 31 62
Low-level vision      2 4—5 60
Machine vision      11
Maclaurian series      84—85
Manual segmentation      5
MAP      8—9 12 19—20 35 38—40 42—43 53 63
Marginal density function      47
Marginal distributions      51
Markov random field      13
Markovian      88
Markovianess      14 23
Maximum entropy      17
Mean field annealing      13
Merge regions      107
Metropolis      24
MLP      8
Modeling images      85
Modular integration      7 11 60—61 69 73—74
Morphometric      6
Mother wavelet      29
MRE      8—9 12—14 18 21—22 35—36 38 43 45 52—53 55 63 67 82—83 86—87
Multifrequency channel      25
Multilayer perceptron      8
Multiple node cliques      114
Multiresolution      6 9 24—25 29 30—31 60—61 69 73—74 78
Multiresolution decomposition      31
Multiresolution framework      60 62 104
Multiscale representations      26
Multivalued variables      85
Navigation      2 11 79
Neighborhood, first order      14 17
Neighborhood, second order      14 17
Neural network      76
Neural networks      8 12—13
Noise      81 113
Non-convex      12 23
Non-stationary signal      29
Normalization      27
normalization constant      14
NP-hard      5 1
Obstacle avoidance      3
Octave      24 26
Optical flow      2
Optimal interpretation      6
Partial derivative      84
Particle Physics      5
Partition      99
Partition function      14 36 83
Partitions      99
PDF      8 44—45 48 51—53 97
Pdf, joint      5 1
Physiology      1
Planar graph      44 63
Point spread function      18
Polar coordinate      113
Posterior distribution      19 21—23
Posterior probability      81—82
Potential function      16 20 22—23
Primary features      101

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