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| Preface | |
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| Contributors | |
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| Introduction | |
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| Components of a vision system | |
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| Imaging systems | |
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| Signal processing for computer vision | |
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| Pattern recognition for computer vision | |
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| Performance evaluation of algorithms | |
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| Classes of tasks | |
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| References | |
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| Sensors and Imaging | |
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| Radiation and Illumination | |
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| Introduction | |
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| Fundamentals of electromagnetic radiation | |
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| Radiometric quantities | |
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| Fundamental concepts of photometry | |
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| Interaction of radiation with matter | |
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| Illumination techniques | |
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| References | |
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| Imaging Optics | |
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| Introduction | |
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| Basic concepts of geometric optics | |
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| Lenses | |
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| Optical properties of glasses | |
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| Aberrations | |
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| Optical image formation | |
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| Wave and Fourier optics | |
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| References | |
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| Radiometry of Imaging | |
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| Introduction | |
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| Observing surfaces | |
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| Propagating radiance | |
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| Radiance of imaging | |
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| Detecting radiance | |
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| Concluding summary | |
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| References | |
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| Solid-State Image Sensing | |
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| Introduction | |
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| Fundamentals of solid-state photosensing | |
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| Photocurrent processing | |
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| Transportation of photosignals | |
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| Electronic signal detection | |
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| Architectures of image sensors | |
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| Color vision and color imaging | |
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| Practical limitations of semiconductor photosensors | |
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| Conclusions | |
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| References | |
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| Geometric Calibration of Digital Imaging Systems | |
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| Introduction | |
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| Calibration terminology | |
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| Parameters influencing geometrical performance | |
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| Optical systems model of image formation | |
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| Camera models | |
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| Calibration and orientation techniques | |
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| Photogrammetric applications | |
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| Summary | |
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| References | |
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| Three-Dimensional Imaging Techniques | |
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| Introduction | |
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| Characteristics of 3-D sensors | |
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| Triangulation | |
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| Time-of-flight (TOF) of modulated light | |
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| Optical Interferometry (OF) | |
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| Conclusion | |
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| References | |
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| Signal Processing and Pattern Recognition | |
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| Representation of Multidimensional Signals | |
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| Introduction | |
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| Continuous signals | |
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| Discrete signals | |
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| Relation between continuous and discrete signals | |
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| Vector spaces and unitary transforms | |
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| Continuous Fourier transform (FT) | |
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| The discrete Fourier transform (DFT) | |
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| Scale of signals | |
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| Scale space and diffusion | |
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| Multigrid representations | |
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| References | |
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| Neighborhood Operators | |
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| Basics | |
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| Linear shift-invariant filters | |
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| Recursive filters | |
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| Classes of nonlinear filters | |
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| Local averaging | |
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| Interpolation | |
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| Edge detection | |
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| Tensor representation of simple neighborhoods | |
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| References | |
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| Motion | |
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| Introduction | |
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| Basics: flow and correspondence | |
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| Optical flow-based motion estimation | |
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| Quadrature filter techniques | |
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| Correlation and matching | |
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| Modeling of flow fields | |
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| References | |
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| Three-Dimensional Imaging Algorithms | |
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| Introduction | |
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| Stereopsis | |
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| Depth-from-focus | |
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| References | |
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| Design of Nonlinear Diffusion Filters | |
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| Introduction | |
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| Filter design | |
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| Parameter selection | |
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| Extensions | |
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| Relations to variational image restoration | |
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| Summary | |
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| References | |
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| Variational Adaptive Smoothing and Segmentation | |
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| Introduction | |
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| Processing of two- and three-dimensional images | |
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| Processing of vector-valued images | |
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| Processing of image sequences | |
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| References | |
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| Morphological Operators | |
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| Introduction | |
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| Preliminaries | |
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| Basic morphological operators | |
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| Advanced morphological operators | |
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| References | |
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| Probabilistic Modeling in Computer Vision | |
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| Introduction | |
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| Why probabilistic models? | |
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| Object recognition as probabilistic modeling | |
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| Model densities | |
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| Practical issues | |
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| Summary, conclusions, and discussion | |
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| References | |
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| Fuzzy Image Processing | |
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| Introduction | |
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| Fuzzy image understanding | |
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| Fuzzy image processing systems | |
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| Theoretical components of fuzzy image processing | |
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| Selected application examples | |
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| Conclusions | |
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| References | |
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| Neural Net Computing for Image Processing | |
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| Introduction | |
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| Multilayer perceptron (MLP) | |
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| Self-organizing neural networks | |
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| Radial-basis neural networks (RBNN) | |
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| Transformation radial-basis networks (TRBNN) | |
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| Hopfield neural networks | |
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| Application examples of neural networks | |
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| Concluding remarks | |
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| References | |
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| Application Gallery | |
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| Application Gallery | |
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| Object Recognition with Intelligent Cameras | |
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| 3-D Image Metrology of Wing Roots | |
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| Quality Control in a Shipyard | |
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| Topographical Maps of Microstructures | |
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| Fast 3-D Full Body Scanning for Humans and Other Objects | |
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| Reverse Engineering Using Optical Range Sensors | |
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| 3-D Surface Reconstruction from Image Sequences | |
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| Motion Tracking | |
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| Tracking "Fuzzy" Storms in Doppler Radar Images | |
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| 3-D Model-Driven Person Detection | |
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| Knowledge-Based Image Retrieval | |
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| Monitoring Living Biomass with in situ Microscopy | |
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| Analyzing Size Spectra of Oceanic Air Bubbles | |
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| Thermography to Measure Water Relations of Plant Leaves | |
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| Small-Scale Air-Sea Interaction with Thermography | |
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| Optical Leaf Growth Analysis | |
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| Analysis of Motility Assay Data | |
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| Fluorescence Imaging of Air-Water Gas Exchange | |
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| Particle-Tracking Velocimetry | |
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| Analyzing Particle Movements at Soil Interfaces | |
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| 3-D Velocity Fields from Flow Tomography Data | |
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| Cloud Classification Analyzing Image Sequences | |
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| No[subscript X] Emissions Retrieved from Satellite Images | |
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| Multicolor Classification of Astronomical Objects | |
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| Model-Based Fluorescence Imaging | |
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| Analyzing the 3-D Genome Topology | |
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| References | |
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| Index | |