模式识别、机器智能与生物特征识别 英文版2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载

模式识别、机器智能与生物特征识别 英文版PDF格式电子书版下载

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PartⅠ：Pattern Recognition and Machine Intelligence3

1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition3

1.1 Introduction3

1.2 Basic Notions of Evolutionary Algorithms4

1.3 A Review of EAs in Pattern Recognition15

1.4 Future Research Directions21

1.5 Conclusions23

References24

2 Pattern Discovery and Recognition in Sequences29

2.1 Introduction29

2.2 Sequence Patterns and Pattern Discovery-A Brief Review31

2.3 Our Pattern Discovery Framework42

2.4 Conclusion58

References58

3 A Hybrid Method of Tone Assessment for Mandarin CALL System61

3.1 Introduction61

3.2 Related Work65

3.3 Proposed Approach67

3.4 Experimental Procedure and Analysis73

3.5 Conclusions77

References78

4 Fusion with Infrared Images for an Improved Performance and Perception81

4.1 Introduction81

4.2 The Principle of Infrared Imaging82

4.3 Fusion with Infrared Images83

4.4 Applications102

4.5 Summary104

References105

5 Feature Selection and Ranking for Pattern Classification in Wireless Sensor Networks109

5.1 Introduction109

5.2 General Approach112

5.3 Sensor Ranking115

5.4 Experiments118

5.5 Summary,Discussion and Conclusions134

References136

6 Principles and Applications of RIDED-2D-A Robust Edge Detection Method in Range Images139

6.1 Introduction140

6.2 Definitions and Analysis143

6.3 Principles of Instantaneous Denoising and Edge Detection146

6.4 Experiments and Evaluations151

6.5 Discussions and Applications159

6.6 Conclusions and Prospects163

References165

PartⅡ：Computer Vision and Image Processing171

7 Lens Shading Correction for Dirt Detection171

7.1 Introduction171

7.2 Background174

7.3 Our Proposed Method180

7.4 Experimental Results184

7.5 Conclusions194

References194

8 Using Prototype-Based Classification for Automatic Knowledge Acquisition197

8.1 Introduction197

8.2 Prototype-Based Classification198

8.3 Methodology204

8.4 Application206

8.5 Results208

8.6 Conclusion211

References211

9 Tracking Deformable Objects with Evolving Templates for Real-Time Machine Vision213

9.1 Introduction213

9.2 Problem Formulation216

9.3 Search Framework for Computing Template Position218

9.4 Updating Framework for Computing Template Changes224

9.5 Multiple Object Tracking and Intensity Information227

9.6 Experiments and Results229

9.7 Conclusions and Future Work233

References234

10 Human Extremity Detection for Action Recognition237

10.1 Introduction237

10.2 Relevant Works239

10.3 Extremities as Points on a Contour241

10.4 Extremities as Image Patches250

10.5 Experimental Results254

10.6 Conclusion258

References259

11 Ensemble Learning for Object Recognition and Tracking261

11.1 Introduction261

11.2 Random Subspace Method264

11.3 Boosting Method269

References276

12 Depth Image Based Rendering279

12.1 Introduction279

12.2 Depth Image Based Rendering283

12.3 Disocclusions289

12.4 Other Challenges304

12.5 Conclusion307

References308

PartⅢ：Face Recognition and Forensics313

13 Gender and Race Identification by Man and Machine313

13.1 Introduction313

13.2 Background314

13.3 Silhouetted Profile Faces315

13.4 Frontal Faces319

13.5 Fusing the Frontal View and Silhouetted Profile View Classifiers323

13.6 Human Experiments324

13.7 Observations and Discussion329

13.8 Concluding Remarks330

References331

14 Common Vector Based Face Recognition Algorithm335

14.1 Introduction335

14.2 Algorithm Description339

14.3 Two Methods Based on Common Vector347

14.4 Experiments and Results350

14.5 Conclusion and Future Research358

References358

15 A Look at Eye Detection for Unconstrained Environments361

15.1 Introduction361

15.2 Related Work363

15.3 Machine Learning Approach364

15.4 Correlation Filter Approach368

15.5 Experiments370

15.6 Conclusions385

References386

16 Kernel Methods for Facial Image Preprocessing389

16.1 Introduction389

16.2 Kernel PCA391

16.3 Kernel Methods for Nonlinear Image Preprocessing392

16.4 Face Image Preprocessing Using KPCA397

16.5 Summary407

References408

17 Fingerprint Identification-Ideas,Influences,and Trends of New Age411

17.1 Introduction411

17.2 System Architecture and Applications of Fingerprint Matching415

17.3 The Early Years419

17.4 Recent Feature Extraction Techniques-Addressing Core Problem423

17.5 Conclusion and Future Directions438

References439

18 Subspaces Versus Submanifolds-A Comparative Study of Face Recognition447

18.1 Introduction447

18.2 Notation and Definitions449

18.3 Brief Review of Subspace-Based Face Recognition Algorithms451

18.4 Submanifold-Based Algorithms for Face Recognition453

18.5 Experiments Results and Analysis472

18.6 Conclusion480

References481

19 Linear and Nonlinear Feature Extraction Approaches for Face Recognition485

19.1 Introduction485

19.2 Linear Feature Extraction Methods488

19.3 Non-Linear Feature Extraction Methods489

19.4 Conclusions511

References512

20 Facial Occlusion Reconstruction Using Direct Combined Model515

20.1 Introduction515

20.2 Direct Combined Model Algorithm518

20.3 Reconstruction System523

20.4 Experimental Results528

20.5 Conclusions530

References530

21 Generative Models and Probability Evaluation for Forensic Evidence533

21.1 Introduction534

21.2 Generative Models of Individuality535

21.3 Application to Birthdays538

21.4 Application to Human Heights540

21.5 Application to Fingerprints544

21.6 Summary557

References559

22 Feature Mining and Pattern Recognition in Multimedia Forensics-Detection of JPEG Image Based Steganography,Double-Compression,Interpolations and WAV Audio Based Steganography561

22.1 Introduction562

22.2 Related Works566

22.3 Statistical Characteristics and Modification568

22.4 Feature Mining for JPEG Image Forensics573

22.5 Derivative Based Audio Steganalysis576

22.6 Pattern Recognition Techniques581

22.7 Experiments584

22.8 Conclusions600

References601

PartⅣ：Biometric Authentication607

23 Biometric Authentication607

23.1 Introduction608

23.2 Basic Operations of a Biometric System616

23.3 Biometrics Standardization621

23.4 Certification of Biometric System622

23.5 Cloud Service—Web Service Authentication624

23.6 Challenges of Large Scale Deployment of Biometric Systems625

23.7 Conclusion628

References630

24 Radical-Based Hybrid Statistical-Structural Approach for Online Handwritten Chinese Character Recognition633

24.1 Introduction633

24.2 Overview of Radical-Based Approach635

24.3 Formation of Radical Models637

24.4 Radical-Based Recognition Framework643

24.5 Experiments650

24.6 Concluding Remarks653

References654

25 Current Trends in Multimodal Biometric System—Rank Level Fusion657

25.1 Introduction657

25.2 Multimodal Biometric System660

25.3 Fusion in Multimodal Biometric System664

25.4 Rank Level Fusion667

25.5 Conclusion672

References672

26 Off-line Signature Verification by Matching with a 3D Reference Knowledge Image—From Research to Actual Application675

26.1 Introduction675

26.2 Used Signature Data676

26.3 Image Types Used for Feature Extraction and Evaluation678

26.4 Skills of Forgery Creation of Used Forgeries680

26.5 Previous Work and Motivation for 3D RKI682

26.6 3D Reference Knowledge of Signature689

26.7 Ammar Matching Technique691

26.8 Feature Extraction694

26.9 Distance Measure and Verification695

26.10 Experimental Results and Discussion696

26.11 Limited Results are Shown and Discussed702

26.12 AMT Features and Signature Recognition703

26.13 AMT and Closely Related Works703

26.14 nansition from Research to Prototyping then Pilot Project and Actual Use704

26.15 Conclusions706

References707

27 Unified Entropy Theory and Maximum Discrimination on Pattern Recognition709

27.1 Introduction709

27.2 Unified Entropy Theory in Pattern Recognition710

27.3 Mutual-Information—Discriminate Entropy in Pattern Recognition715

27.4 Mutual Information Discrimination Analysis in Pattern Recognition717

27.5 Maximum MI principle719

27.6 Maximum MI Discriminate SubSpace Recognition in Handwritten Chinese Character Recognition721

27.7 Conclusion725

References731

28 Fundamentals of Biometrics—Hand Written Signature and Iris733

28.1 Prologue733

28.2 Fundamentals of Handwritten Signature735

28.3 Acquisition750

28.4 Databases751

28.5 Signature Analysers752

28.6 Off-line Methods754

28.7 On-line Methods756

28.8 Fundamentals of Iris760

28.9 Feature Extraction764

28.10 Preprocessing771

28.11 Iris Image Databases776

28.12 Iris Analyzers776

28.13 Conclusion780

References781

29 Recent Trends in Iris Recognition785

29.1 Introduction785

29.2 Basic Modules of Iris Recognition786

29.3 Performance Measures789

29.4 Limitations of Current Techniques791

29.5 Future Scope792

References793

30 Using Multisets of Features and Interactive Feature Selection to Get Best Qualitative Performance for Automatic Signature Verification797

30.1 Introduction797

30.2 Signature Data799

30.3 ASV Systems Using Threshold-Based Decision801

30.4 MSF and Its Performance807

30.5 IFS and QP813

30.6 Conclusion819

References819

31 Fourier Transform in Numeral Recognition and Signature Verification823

31.1 Concepts of Digital Transforms823

31.2 Orthonormal System of Trigonometric Functions824

31.3 Introduction to Discrete Fourier Transform828

31.4 Properties of DFT830

31.5 DFT Calculation Problem833

31.6 Description of a Numeral Through Fourier Coefficents837

31.7 Numeral Recognition Through Fourier Transform842

31.8 Signature Verification Systems Trough Fourier Analysis847

31.9 On-line Signature Verification System Based on Fourier Analysis of Strokes851

References854

Index859