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PartⅠ：Pattern Recognition and Machine Intelligence 3

1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition 3

1.1 Introduction 3

1.2 Basic Notions of Evolutionary Algorithms 4

1.3 A Review of EAs in Pattern Recognition 15

1.4 Future Research Directions 21

1.5 Conclusions 23

References 24

2 Pattern Discovery and Recognition in Sequences 29

2.1 Introduction 29

2.2 Sequence Patterns and Pattern Discovery-A Brief Review 31

2.3 Our Pattern Discovery Framework 42

2.4 Conclusion 58

References 58

3 A Hybrid Method of Tone Assessment for Mandarin CALL System 61

3.1 Introduction 61

3.2 Related Work 65

3.3 Proposed Approach 67

3.4 Experimental Procedure and Analysis 73

3.5 Conclusions 77

References 78

4 Fusion with Infrared Images for an Improved Performance and Perception 81

4.1 Introduction 81

4.2 The Principle of Infrared Imaging 82

4.3 Fusion with Infrared Images 83

4.4 Applications 102

4.5 Summary 104

References 105

5 Feature Selection and Ranking for Pattern Classification in Wireless Sensor Networks 109

5.1 Introduction 109

5.2 General Approach 112

5.3 Sensor Ranking 115

5.4 Experiments 118

5.5 Summary,Discussion and Conclusions 134

References 136

6 Principles and Applications of RIDED-2D-A Robust Edge Detection Method in Range Images 139

6.1 Introduction 140

6.2 Definitions and Analysis 143

6.3 Principles of Instantaneous Denoising and Edge Detection 146

6.4 Experiments and Evaluations 151

6.5 Discussions and Applications 159

6.6 Conclusions and Prospects 163

References 165

PartⅡ：Computer Vision and Image Processing 171

7 Lens Shading Correction for Dirt Detection 171

7.1 Introduction 171

7.2 Background 174

7.3 Our Proposed Method 180

7.4 Experimental Results 184

7.5 Conclusions 194

References 194

8 Using Prototype-Based Classification for Automatic Knowledge Acquisition 197

8.1 Introduction 197

8.2 Prototype-Based Classification 198

8.3 Methodology 204

8.4 Application 206

8.5 Results 208

8.6 Conclusion 211

References 211

9 Tracking Deformable Objects with Evolving Templates for Real-Time Machine Vision 213

9.1 Introduction 213

9.2 Problem Formulation 216

9.3 Search Framework for Computing Template Position 218

9.4 Updating Framework for Computing Template Changes 224

9.5 Multiple Object Tracking and Intensity Information 227

9.6 Experiments and Results 229

9.7 Conclusions and Future Work 233

References 234

10 Human Extremity Detection for Action Recognition 237

10.1 Introduction 237

10.2 Relevant Works 239

10.3 Extremities as Points on a Contour 241

10.4 Extremities as Image Patches 250

10.5 Experimental Results 254

10.6 Conclusion 258

References 259

11 Ensemble Learning for Object Recognition and Tracking 261

11.1 Introduction 261

11.2 Random Subspace Method 264

11.3 Boosting Method 269

References 276

12 Depth Image Based Rendering 279

12.1 Introduction 279

12.2 Depth Image Based Rendering 283

12.3 Disocclusions 289

12.4 Other Challenges 304

12.5 Conclusion 307

References 308

PartⅢ：Face Recognition and Forensics 313

13 Gender and Race Identification by Man and Machine 313

13.1 Introduction 313

13.2 Background 314

13.3 Silhouetted Profile Faces 315

13.4 Frontal Faces 319

13.5 Fusing the Frontal View and Silhouetted Profile View Classifiers 323

13.6 Human Experiments 324

13.7 Observations and Discussion 329

13.8 Concluding Remarks 330

References 331

14 Common Vector Based Face Recognition Algorithm 335

14.1 Introduction 335

14.2 Algorithm Description 339

14.3 Two Methods Based on Common Vector 347

14.4 Experiments and Results 350

14.5 Conclusion and Future Research 358

References 358

15 A Look at Eye Detection for Unconstrained Environments 361

15.1 Introduction 361

15.2 Related Work 363

15.3 Machine Learning Approach 364

15.4 Correlation Filter Approach 368

15.5 Experiments 370

15.6 Conclusions 385

References 386

16 Kernel Methods for Facial Image Preprocessing 389

16.1 Introduction 389

16.2 Kernel PCA 391

16.3 Kernel Methods for Nonlinear Image Preprocessing 392

16.4 Face Image Preprocessing Using KPCA 397

16.5 Summary 407

References 408

17 Fingerprint Identification-Ideas,Influences,and Trends of New Age 411

17.1 Introduction 411

17.2 System Architecture and Applications of Fingerprint Matching 415

17.3 The Early Years 419

17.4 Recent Feature Extraction Techniques-Addressing Core Problem 423

17.5 Conclusion and Future Directions 438

References 439

18 Subspaces Versus Submanifolds-A Comparative Study of Face Recognition 447

18.1 Introduction 447

18.2 Notation and Definitions 449

18.3 Brief Review of Subspace-Based Face Recognition Algorithms 451

18.4 Submanifold-Based Algorithms for Face Recognition 453

18.5 Experiments Results and Analysis 472

18.6 Conclusion 480

References 481

19 Linear and Nonlinear Feature Extraction Approaches for Face Recognition 485

19.1 Introduction 485

19.2 Linear Feature Extraction Methods 488

19.3 Non-Linear Feature Extraction Methods 489

19.4 Conclusions 511

References 512

20 Facial Occlusion Reconstruction Using Direct Combined Model 515

20.1 Introduction 515

20.2 Direct Combined Model Algorithm 518

20.3 Reconstruction System 523

20.4 Experimental Results 528

20.5 Conclusions 530

References 530

21 Generative Models and Probability Evaluation for Forensic Evidence 533

21.1 Introduction 534

21.2 Generative Models of Individuality 535

21.3 Application to Birthdays 538

21.4 Application to Human Heights 540

21.5 Application to Fingerprints 544

21.6 Summary 557

References 559

22 Feature Mining and Pattern Recognition in Multimedia Forensics-Detection of JPEG Image Based Steganography,Double-Compression,Interpolations and WAV Audio Based Steganography 561

22.1 Introduction 562

22.2 Related Works 566

22.3 Statistical Characteristics and Modification 568

22.4 Feature Mining for JPEG Image Forensics 573

22.5 Derivative Based Audio Steganalysis 576

22.6 Pattern Recognition Techniques 581

22.7 Experiments 584

22.8 Conclusions 600

References 601

PartⅣ：Biometric Authentication 607

23 Biometric Authentication 607

23.1 Introduction 608

23.2 Basic Operations of a Biometric System 616

23.3 Biometrics Standardization 621

23.4 Certification of Biometric System 622

23.5 Cloud Service—Web Service Authentication 624

23.6 Challenges of Large Scale Deployment of Biometric Systems 625

23.7 Conclusion 628

References 630

24 Radical-Based Hybrid Statistical-Structural Approach for Online Handwritten Chinese Character Recognition 633

24.1 Introduction 633

24.2 Overview of Radical-Based Approach 635

24.3 Formation of Radical Models 637

24.4 Radical-Based Recognition Framework 643

24.5 Experiments 650

24.6 Concluding Remarks 653

References 654

25 Current Trends in Multimodal Biometric System—Rank Level Fusion 657

25.1 Introduction 657

25.2 Multimodal Biometric System 660

25.3 Fusion in Multimodal Biometric System 664

25.4 Rank Level Fusion 667

25.5 Conclusion 672

References 672

26 Off-line Signature Verification by Matching with a 3D Reference Knowledge Image—From Research to Actual Application 675

26.1 Introduction 675

26.2 Used Signature Data 676

26.3 Image Types Used for Feature Extraction and Evaluation 678

26.4 Skills of Forgery Creation of Used Forgeries 680

26.5 Previous Work and Motivation for 3D RKI 682

26.6 3D Reference Knowledge of Signature 689

26.7 Ammar Matching Technique 691

26.8 Feature Extraction 694

26.9 Distance Measure and Verification 695

26.10 Experimental Results and Discussion 696

26.11 Limited Results are Shown and Discussed 702

26.12 AMT Features and Signature Recognition 703

26.13 AMT and Closely Related Works 703

26.14 nansition from Research to Prototyping then Pilot Project and Actual Use 704

26.15 Conclusions 706

References 707

27 Unified Entropy Theory and Maximum Discrimination on Pattern Recognition 709

27.1 Introduction 709

27.2 Unified Entropy Theory in Pattern Recognition 710

27.3 Mutual-Information—Discriminate Entropy in Pattern Recognition 715

27.4 Mutual Information Discrimination Analysis in Pattern Recognition 717

27.5 Maximum MI principle 719

27.6 Maximum MI Discriminate SubSpace Recognition in Handwritten Chinese Character Recognition 721

27.7 Conclusion 725

References 731

28 Fundamentals of Biometrics—Hand Written Signature and Iris 733

28.1 Prologue 733

28.2 Fundamentals of Handwritten Signature 735

28.3 Acquisition 750

28.4 Databases 751

28.5 Signature Analysers 752

28.6 Off-line Methods 754

28.7 On-line Methods 756

28.8 Fundamentals of Iris 760

28.9 Feature Extraction 764

28.10 Preprocessing 771

28.11 Iris Image Databases 776

28.12 Iris Analyzers 776

28.13 Conclusion 780

References 781

29 Recent Trends in Iris Recognition 785

29.1 Introduction 785

29.2 Basic Modules of Iris Recognition 786

29.3 Performance Measures 789

29.4 Limitations of Current Techniques 791

29.5 Future Scope 792

References 793

30 Using Multisets of Features and Interactive Feature Selection to Get Best Qualitative Performance for Automatic Signature Verification 797

30.1 Introduction 797

30.2 Signature Data 799

30.3 ASV Systems Using Threshold-Based Decision 801

30.4 MSF and Its Performance 807

30.5 IFS and QP 813

30.6 Conclusion 819

References 819

31 Fourier Transform in Numeral Recognition and Signature Verification 823

31.1 Concepts of Digital Transforms 823

31.2 Orthonormal System of Trigonometric Functions 824

31.3 Introduction to Discrete Fourier Transform 828

31.4 Properties of DFT 830

31.5 DFT Calculation Problem 833

31.6 Description of a Numeral Through Fourier Coefficents 837

31.7 Numeral Recognition Through Fourier Transform 842

31.8 Signature Verification Systems Trough Fourier Analysis 847

31.9 On-line Signature Verification System Based on Fourier Analysis of Strokes 851

References 854

Index 859