Computer vision and applications

Cover......Page 1
Preface......Page 12
Contributors......Page 16
Components of a vision system......Page 24
Imaging systems......Page 25
Signal processing for computer vision......Page 26
Pattern recognition for computer vision......Page 27
Performance evaluation of algorithms......Page 28
Classes of tasks......Page 29
References......Page 31
I Sensors and Imaging......Page 32
Radiation and Illumination......Page 34
Introduction......Page 35
Fundamentals of electromagnetic radiation......Page 36
Radiometric quantities......Page 40
Fundamental concepts of photometry......Page 50
Interaction of radiation with matter......Page 54
Illumination techniques......Page 69
References......Page 74
Imaging Optics......Page 76
Basic concepts of geometric optics......Page 77
Lenses......Page 79
Optical properties of glasses......Page 89
Aberrations......Page 90
Optical image formation......Page 98
Wave and Fourier optics......Page 103
References......Page 107
Introduction......Page 108
Observing surfaces......Page 109
Propagating radiance......Page 111
Radiance of imaging......Page 114
Detecting radiance......Page 117
Concluding summary......Page 131
References......Page 132
Solid-State Image Sensing......Page 134
Introduction......Page 135
Fundamentals of solid-state photosensing......Page 136
Photocurrent processing......Page 143
Transportation of photosignals......Page 150
Electronic signal detection......Page 153
Architectures of image sensors......Page 157
Color vision and color imaging......Page 162
Practical limitations of semiconductor photosensors......Page 169
Conclusions......Page 171
References......Page 172
Introduction......Page 176
Calibration terminology......Page 177
Parameters influencing geometrical performance......Page 178
Optical systems model of image formation......Page 180
Camera models......Page 181
Calibration and orientation techniques......Page 186
Photogrammetric applications......Page 193
References......Page 196
Three-Dimensional Imaging Techniques......Page 200
Introduction......Page 201
Characteristics of 3-D sensors......Page 202
Triangulation......Page 205
Time-of-flight (TOF) of modulated light......Page 219
Optical Interferometry (OF)......Page 222
References......Page 228
II Signal Processing and Pattern Recognition......Page 232
Representation of Multidimensional Signals......Page 234
Continuous signals......Page 235
Discrete signals......Page 238
Relation between continuous and discrete signals......Page 247
Vector spaces and unitary transforms......Page 255
Continuous Fourier transform (FT)......Page 260
The discrete Fourier transform (DFT)......Page 269
Scale of signals......Page 275
Scale space and diffusion......Page 283
Multigrid representations......Page 290
References......Page 294
Neighborhood Operators......Page 296
Basics......Page 297
Linear shift-invariant filters......Page 301
Recursive filters......Page 308
Classes of nonlinear filters......Page 315
Local averaging......Page 319
Interpolation......Page 334
Edge detection......Page 348
Tensor representation of simple neighborhoods......Page 358
References......Page 367
Introduction......Page 370
Basics: flow and correspondence......Page 372
Optical flow-based motion estimation......Page 381
Quadrature filter techniques......Page 395
Correlation and matching......Page 402
Modeling of flow fields......Page 405
References......Page 415
Introduction......Page 420
Stereopsis......Page 421
Depth-from-focus......Page 437
References......Page 458
Introduction......Page 462
Filter design......Page 463
Parameter selection......Page 471
Extensions......Page 474
Relations to variational image restoration......Page 475
References......Page 477
Introduction......Page 482
Processing of two- and three-dimensional images......Page 486
Processing of vector-valued images......Page 497
Processing of image sequences......Page 499
References......Page 503
Introduction......Page 506
Preliminaries......Page 507
Basic morphological operators......Page 512
Advanced morphological operators......Page 518
References......Page 538
Introduction......Page 540
Why probabilistic models?......Page 541
Object recognition as probabilistic modeling......Page 542
Model densities......Page 547
Practical issues......Page 559
Summary, conclusions, and discussion......Page 561
References......Page 562
Introduction......Page 564
Fuzzy image understanding......Page 571
Fuzzy image processing systems......Page 576
Theoretical components of fuzzy image processing......Page 579
Selected application examples......Page 587
Conclusions......Page 593
References......Page 594
Introduction......Page 600
Multilayer perceptron (MLP)......Page 602
Self-organizing neural networks......Page 608
Radial-basis neural networks (RBNN)......Page 613
Transformation radial-basis networks (TRBNN)......Page 616
Hopfield neural networks......Page 619
Application examples of neural networks......Page 624
Concluding remarks......Page 627
References......Page 628
III Application Gallery......Page 632
Object Recognition with Intelligent Cameras......Page 633
3-D Image Metrology of Wing Roots......Page 635
Quality Control in a Shipyard......Page 637
Topographical Maps of Microstructures......Page 639
Fast 3-D Full Body Scanning for Humans and Other Objects......Page 641
Reverse Engineering Using Optical Range Sensors......Page 643
3-D Surface Reconstruction from Image Sequences......Page 645
Motion Tracking......Page 647
Tracking ``Fuzzy\'\' Storms in Doppler Radar Images......Page 649
3-D Model-Driven Person Detection......Page 651
Knowledge-Based Image Retrieval......Page 653
Monitoring Living Biomass with in situ Microscopy......Page 655
Analyzing Size Spectra of Oceanic Air Bubbles......Page 657
Thermography to Measure Water Relations of Plant Leaves......Page 659
Small-Scale Air-Sea Interaction with Thermography......Page 661
Optical Leaf Growth Analysis......Page 663
Analysis of Motility Assay Data......Page 665
Fluorescence Imaging of Air-Water Gas Exchange......Page 667
Particle-Tracking Velocimetry......Page 669
Analyzing Particle Movements at Soil Interfaces......Page 671
3-D Velocity Fields from Flow Tomography Data......Page 673
Cloud Classification Analyzing Image Sequences......Page 675
NOX Emissions Retrieved from Satellite Images......Page 677
Multicolor Classification of Astronomical Objects......Page 679
Model-Based Fluorescence Imaging......Page 681
Analyzing the 3-D Genome Topology......Page 683
References......Page 685
Index......Page 690