Sadjadi / Javidi Physics of Automatic Target Recognition

1. Auflage 2007
ISBN: 978-0-387-36943-3
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 3, 250 Seiten

Reihe: Advanced Sciences and Technologies for Security Applications

This book examines the roles of sensors, physics-based attributes, classification methods, and performance evaluation in automatic target recognition. It details target classification from small mine-like objects to large tactical vehicles. Also explored in the book are invariants of sensor and transmission transformations, which are crucial in the development of low latency and computationally manageable automatic target recognition systems.

Autoren/Hrsg.

Sadjadi, Firooz

Javidi, Bahram

Inhaltsverzeichnis

1;Contents;7
2;Preface;9
3;Contributors;10
4;Kernel-Based Nonlinear Subspace Target Detection for Hyperspectral Imagery;12
4.1;1.1 Introduction;12
4.2;1.2 Kernel Methods and Kernel Trick;13
4.3;1.3 Linear Matched Subspace Detector and Kernel Matched Subspace Detector;14
4.4;1.4 OSP and Kernel OSP Algorithms;18
4.5;1.5 Linear Spectral Matched Filter and Kernel Spectral Matched Filter;21
4.6;1.6 Adaptive Subspace Detector and Kernel Adaptive Subspace Detector;23
4.7;1.7 Experimental Results;25
4.8;1.8 Conclusions;29
4.9;1.9 Appendix I (Kernel PCA);31
4.10;References;34
5;Theory of Invariant Algebra and Its Use in Automatic Target Recognition;36
5.1;2.1 Introduction;36
5.2;2.2 Theory of Invariant Alagebra;37
5.3;2.3 Applications of Invariants of Binary Quantics;39
5.4;2.4 Invariant of Ternary Quantics;43
5.5;2.5 Complexity Analysis;46
5.6;2.6 Summary;50
5.7;References;51
6;Automatic Recognition of Underground Targets Using Time– Frequency Analysis and Optimization Techniques;52
6.1;3.1 Introduction;52
6.2;3.2 Theoretical Models;54
6.3;3.3 Classification of Test Field Targets;59
6.4;3.4 Summary and Conclusions;65
6.5;Acknowledgements;66
6.6;References;66
7;A Weighted Zak Transform, Its Properties, and Applications to Signal Processing;68
7.1;4.1 Introduction;68
7.2;4.2 Background and Definitions;69
7.3;4.3 The Weighted Zak Transform and the Ambiguity Function;70
7.4;4.4 The Weighting Function;72
7.5;4.5 The Inverse of the Weighted Zak Transform;75
7.6;4.6 Signal Synthesis Using the Weighted Zak Transform;81
7.7;Acknowledgment;82
7.8;References;82
8;Using Polarization Features of Visible Light for Automatic Landmine Detection;83
8.1;5.1 Introduction;83
8.2;5.2 Landmine Detection with Camera Systems;83
8.3;5.3 Detection;85
8.4;5.4 Detection Tests;88
8.5;5.5 Test Results;93
8.6;5.6 Conclusions;98
8.7;References;99
9;The Physics of Polarization-Sensitive Optical Imaging;101
9.1;6.1 Introduction;101
9.2;6.2 Stokes Vectors and Mueller Matrices;102
9.3;6.3 Target Shape Information from Polarization Imaging;102
9.4;6.4 Summary;113
9.5;References;113
10;Dispersion, Its Effects, and Compensation;115
10.1;7.1 Introduction;115
10.2;7.2 Basic Ideas and Definitions;117
10.3;7.3 Spatial Moments of a Pulse;118
10.4;7.4 Dispersion-Invariant Moments;122
10.5;7.5 Example;124
10.6;7.6 Wigner Approximation for Wave Propagation, and Approximately Invariant Moments;128
10.7;7.7 Dual Case: Initially Given u(0, t);130
10.8;7.8 Conclusion;134
10.9;Acknowledgment;135
10.10;References;135
11;Multisensor Target Recognition in Image Response Space Using Evolutionary Algorithms;136
11.1;8.1 Introduction;136
11.2;8.2 Hybrid Model of Evolutionary Algorithm in Target Recognition with Different Imagery Types;138
11.3;8.3 Computational Experiments with Different Imagery Types;141
11.4;8.4 Conclusions;148
11.5;Acknowledgement;149
11.6;References;149
12;Biophysics of the Eye in Computer Vision: Methods and Advanced Technologies;151
12.1;9.1 Chapter Overview;151
12.2;9.2 Background Review: Light, Eye Responses, and Movements;153
12.3;9.3 Eye Appearance Changes;156
12.4;9.4 Eye Image Representation;158
12.5;9.5 Modeling of the Eye Variability;159
12.6;9.6 Automatic Eye Localization;161
12.7;9.7 Tracking Problem Formulation;164
12.8;9.8 Models of Tracking Methods;166
12.9;9.9 Particle Filter-Based Eye Tracking Methods;167
12.10;9.10 Advanced Eye Tracking–Based Technologies;176
12.11;9.11 Conclusion;178
12.12;References;178
13;Two Approaches to 3D Microorganism Recognition Using Single Exposure Online ( SEOL) Digital Holography;183
13.1;10.1 Introduction;183
13.2;10.2 Single Exposure Online (SEOL) Digital Holography;185
13.3;10.3 3D Morphology-Based Recognition;187
13.4;10.4 Shape-Tolerant 3D Recognition;189
13.5;10.5 Experimental Results;193
13.6;10.6 Conclusion;200
13.7;References;200
14;Distortion-Tolerant 3D Object Recognition by Using Single Exposure On- Axis Digital Holography;203
14.1;11.1 Introduction;203
14.2;11.2 Single Exposure On-Axis Digital Holography;204
14.3;11.3 Composite Filter Design;206
14.4;11.4 Experimental Results;207
14.5;11.5 Conclusion;213
14.6;References;214
15;Design of Distortion-Invariant Optical ID Tags for Remote Identification and Verification of Objects;215
15.1;12.1 Introduction;215
15.2;12.2 Authentication System;216
15.3;12.3 Signature Encryption and Decryption;217
15.4;12.4 Distortion-Invariant ID Tags;219
15.5;12.5 Signature Verification;224
15.6;12.6 Authentication Results;225
15.7;12.7 Conclusions;232
15.8;References;232
16;Speckle Elimination With a Maximum Likelihood Estimation and an Isoline Regularization;235
16.1;13.1 Presentation;235
16.2;13.2 Description of the Algorithm;236
16.3;13.3 Results and Influence of the Parameters;243
16.4;13.4 Conclusion;249
16.5;Acknowledgment;250
16.6;References;250
17;Index;252