Richard D. Juday, Chair/editor ; Sponsored By Spie--the International Society For Optical Engineering ; Cooperating Organizations, Applied Optics Laboratory/new Mexico State University ... [et Al.]. Includes Bibliographies And Index.

Digital And Optical Shape Representation And Pattern Recognition/spie 938 (proceedings Of Spie--the International Society For Optical Engineering)

Proceedings of SPIE-The International Society for Optical Engineering Volume 938·Digital and Optical Shape Representation and Pattern Recognition

Digital and optical shape representation and pattern recognition : 4-6 April 1988, Orlando, Florida

Richard D Juday; Society of Photo-optical Instrumentation Engineers.; New Mexico State University. Applied Optics Laboratory

Juday, Richard D; Society of Photo-optical Instrumentation Engineers

SPIE-The International Society for Optical Engineering

Bellingham, Wash., USA: SPIE

Society Of Photo Optical

Proceedings of SPIE--the International Society for Optical Engineering, v. 938, Bellingham, Wash., USA, c1988

United States, United States of America

Volume 938, 1988

August 1988

Cut-off text on some pages due too tight binding.

Includes bibliographies and index.

contributor: 浙江大学

format: Image/Djvu(.djvu)

unit_name: 浙江大学

Type: 英文图书

Bookmarks:
1. (p1) Session 1 Correlator Architectures
1.1. (p2) Operation Of A Deformable Mirror Device As A Fourier Plane Phase Modulating Filter
1.2. (p11) Edge Enhancement Preprocessing Using Liquid Crystal Televisions
1.3. (p15) Optical Laboratory Comparison Of Computer Generated Holograms For Correlation Matched Spatial Filters
1.4. (p29) Optical Correlator Guidance Technology Demonstration
1.5. (p36) Optical Aberrations Of Correlators
1.6. (p40) Two Variants Of The Optical Correlation Process
1.7. (p48) Highly Multiplexed Optical Correlation Filters
1.8. (p52) Massively Parallel Optical Data Base Management
1.9. (p55) A High Dynamic Range Acousto-Optic Image Correlator For Real-Time Pattern Recognition
1.10. (p66) Comparison Of Bipolar Joint Transform Image Correlators And Phase-Only Matched Filter Correlators
2. (p77) Session 2 Digital Stereo
2.1. (p78) 3-D Sensing With Polar Exponential Sensor Arrays
2.2. (p88) Parallel Environment For Structural Analysis Of Range Imagery
2.3. (p96) Determining Vehicle Motion From Stereo Image Sequences Topographic Labs
2.4. (p101) Finding Wheels Of Vehicles In Stereo Images
2.5. (p109) Disparity Coding-An Approach For Stereo Reconstruction
3. (p121) Session 3 Geometric Image Transformations and Applications
3.1. (p122) A Programmable Video Image Remapper
3.2. (p129) Exponential Sensor Array Geometry And Simulation
3.3. (p138) Motion Stereo And Ego-Motion Complex Logarithmic Mapping (Eclm)
3.4. (p146) Geometric Representation Of Visual Data In The Cortex Of Primates:Computer Reconstruction And Modeling Of Neo-Cortical Map And Column Systems
3.5. (p154) Method And Analysis For Obtaining A Dual Representation Of Images
3.6. (p163) Some Examples Of Image Warping For Low Vision Prosthesis
4. (p169) Session 3 (Continued) Topics in Pattern Recognition
4.1. (p170) Hybrid Optical/Electronic Pattern Recognition With Both Coherent And Noncoherent Operations
4.2. (p178) Feature Tracking And Mapping On The Spatiotemporal Surface
5. (p189) Session 4 Filtering Algorithms
5.1. (p190) Correlation Filters For Orientation Estimation
5.2. (p198) Convolution-Controlled Rotation And Scale Invariance In Optical Correlation
5.3. (p206) New Formulations For Discrete-Valued Correlation Filters
5.4. (p212) Optical Processing Of Imaging Spectrometer Data
5.5. (p221) Pattern Recognition With Undersampled Holograms
5.6. (p230) Is The Information Capacity Of Holography Certainly More Than That Of Photography?
5.7. (p238) Dna Sequence Analysis By Optical Pattern Recognition
5.8. (p246) Characterization Of Corneal Specular Endothelial Photomicrographs By Their Fourier Transforms
5.9. (p253) Extension Of Synthetic Estimation Filters For Relative Position Measurements
5.10. (p261) Amplitude Encoded Binary Phase-Only Filters
5.11. (p266) Analysis Of Binarized Hartley Phase-Only Filter Performance With Respect To Stochastic Noise
6. (p281) Session 5 Object Detection and Classification
6.1. (p282) Object Detection Using Region Growing In Laser Range Imagery
6.2. (p289) Feature Extraction For Undersampled Objects In Range Imagery
6.3. (p295) PSRI Target Recognition in Range Imagery Using Neural Networks
6.4. (p302) Hybrid Associative Memories And Metric Data Models
6.5. (p317) Maximum-Likelihood Image Classification
6.6. (p322) Recognition Of Three-Dimensional Objects Using Linear Prediction
6.7. (p330) Clustering With The Relational C-Means Algorithms Using Different Measures Of Pairwise Distance
7. (p339) Session 6 Representation of Shape
7.1. (p340) A morphological Machine
7.2. (p348) AN Integral Measure Signature For Recognition Of Shapes
7.3. (p357) Recognition Of 3d Curves Based On Curvature And Torsion
7.4. (p365) Monte Carlo Estimation Of Moment Invariants For Pattern Recognition
7.5. (p372) Group Direction Difference Chain Codes For The Representation Of The Border
7.6. (p377) Scale-Varying Representations For Object Recognition
7.7. (p384) Morphological Operator Distributions Based On Monotonicity And The Problem Posed By Digital Disk-Shaped Structuring Elements
8. (p393) Session 7 Model-Based Object Recognition
8.1. (p394) Toward Automatic Generation Of Object Recognition Program-Modeling Sensors
8.2. (p408) A Computer Aided Design-Model-Based System For Object Localization
8.3. (p419) A primitive-Based 3d Object Recognition System
8.4. (p428) CAGD Based Computer Vision
8.5. (p436) CAD BASED OBIECT RECOGNITION:INCORPORATING METRIC AND TOPOLOGICAL INFORMATION
8.6. (p444) Model-Based Vision By Cooperative Processing Of Evidence And Hypotheses Using Configuration Spaces
8.7. (p454) Representation Of 3-D Objects Using Nonrigid Connection Of Components
8.8. (p465) Representing Shape Primitives In Neural Networks

viii, 479 p. : 28 cm
Includes bibliographies and index

2024-07-01