PartⅠ：Pattern Recognition and Machine Intelligence

1 A Review of Applications of Evolutionary Algorithms in Pattern Recognition

1.1 Introduction

1.2 Basic Notions of Evolutionary Algorithms

1.3 A Review of EAs in Pattern Recognition

1.4 Future Research Directions

1.5 Conclusions

References

2 Pattern Discovery and Recognition in Sequences

2.1 Introduction

2.2 Sequence Patterns and Pattern Discovery-A Brief Review

2.3 Our Pattern Discovery Framework

2.4 Conclusion

References

3 A Hybrid Method of Tone Assessment for Mandarin CALL System

3.1 Introduction

3.2 Related Work

3.3 Proposed Approach

3.4 Experimental Procedure and Analysis

3.5 Conclusions

References

4 Fusion with Infrared Images for an Improved Performance and Perception

4.1 Introduction

4.2 The Principle of Infrared Imaging

4.3 Fusion with Infrared Images

4.4 Applications

4.5 Summary

References

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

5.1 Introduction

5.2 General Approach

5.3 Sensor Ranking

5.4 Experiments

5.5 Summary,Discussion and Conclusions

References

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

6.1 Introduction

6.2 Definitions and Analysis

6.3 Principles of Instantaneous Denoising and Edge Detection

6.4 Experiments and Evaluations

6.5 Discussions and Applications

6.6 Conclusions and Prospects

References

PartⅡ：Computer Vision and Image Processing

7 Lens Shading Correction for Dirt Detection

7.1 Introduction

7.2 Background

7.3 Our Proposed Method

7.4 Experimental Results

7.5 Conclusions

References

8 Using Prototype-Based Classification for Automatic Knowledge Acquisition

8.1 Introduction

8.2 Prototype-Based Classification

8.3 Methodology

8.4 Application

8.5 Results

8.6 Conclusion

References

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

9.1 Introduction

9.2 Problem Formulation

9.3 Search Framework for Computing Template Position

9.4 Updating Framework for Computing Template Changes

9.5 Multiple Object Tracking and Intensity Information

9.6 Experiments and Results

9.7 Conclusions and Future Work

References

10 Human Extremity Detection for Action Recognition

10.1 Introduction

10.2 Relevant Works

10.3 Extremities as Points on a Contour

10.4 Extremities as Image Patches

10.5 Experimental Results

10.6 Conclusion

References

11 Ensemble Learning for Object Recognition and Tracking

11.1 Introduction

11.2 Random Subspace Method

11.3 Boosting Method

References

12 Depth Image Based Rendering

12.1 Introduction

12.2 Depth Image Based Rendering

12.3 Disocclusions

12.4 Other Challenges

12.5 Conclusion

References

PartⅢ：Face Recognition and Forensics

13 Gender and Race Identification by Man and Machine

13.1 Introduction

13.2 Background

13.3 Silhouetted Profile Faces

13.4 Frontal Faces

13.5 Fusing the Frontal View and Silhouetted Profile View Classifiers

13.6 Human Experiments

13.7 Observations and Discussion

13.8 Concluding Remarks

References

14 Common Vector Based Face Recognition Algorithm

14.1 Introduction

14.2 Algorithm Description

14.3 Two Methods Based on Common Vector

14.4 Experiments and Results

14.5 Conclusion and Future Research

References

15 A Look at Eye Detection for Unconstrained Environments

15.1 Introduction

15.2 Related Work

15.3 Machine Learning Approach

15.4 Correlation Filter Approach

15.5 Experiments

15.6 Conclusions

References

16 Kernel Methods for Facial Image Preprocessing

16.1 Introduction

16.2 Kernel PCA

16.3 Kernel Methods for Nonlinear Image Preprocessing

16.4 Face Image Preprocessing Using KPCA

16.5 Summary

References

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

17.1 Introduction

17.2 System Architecture and Applications of Fingerprint Matching

17.3 The Early Years

17.4 Recent Feature Extraction Techniques-Addressing Core Problem

17.5 Conclusion and Future Directions

References

18 Subspaces Versus Submanifolds-A Comparative Study of Face Recognition

18.1 Introduction

18.2 Notation and Definitions

18.3 Brief Review of Subspace-Based Face Recognition Algorithms

18.4 Submanifold-Based Algorithms for Face Recognition

18.5 Experiments Results and Analysis

18.6 Conclusion

References

19 Linear and Nonlinear Feature Extraction Approaches for Face Recognition

19.1 Introduction

19.2 Linear Feature Extraction Methods

19.3 Non-Linear Feature Extraction Methods

19.4 Conclusions

References

20 Facial Occlusion Reconstruction Using Direct Combined Model

20.1 Introduction

20.2 Direct Combined Model Algorithm

20.3 Reconstruction System

20.4 Experimental Results

20.5 Conclusions

References

21 Generative Models and Probability Evaluation for Forensic Evidence

21.1 Introduction

21.2 Generative Models of Individuality

21.3 Application to Birthdays

21.4 Application to Human Heights

21.5 Application to Fingerprints

21.6 Summary

References

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

22.1 Introduction

22.2 Related Works

22.3 Statistical Characteristics and Modification

22.4 Feature Mining for JPEG Image Forensics

22.5 Derivative Based Audio Steganalysis

22.6 Pattern Recognition Techniques

22.7 Experiments

22.8 Conclusions

References

PartⅣ：Biometric Authentication

23 Biometric Authentication

23.1 Introduction

23.2 Basic Operations of a Biometric System

23.3 Biometrics Standardization

23.4 Certification of Biometric System

23.5 Cloud Service—Web Service Authentication

23.6 Challenges of Large Scale Deployment of Biometric Systems

23.7 Conclusion

References

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

24.1 Introduction

24.2 Overview of Radical-Based Approach

24.3 Formation of Radical Models

24.4 Radical-Based Recognition Framework

24.5 Experiments

24.6 Concluding Remarks

References

25 Current Trends in Multimodal Biometric System—Rank Level Fusion

25.1 Introduction

25.2 Multimodal Biometric System

25.3 Fusion in Multimodal Biometric System

25.4 Rank Level Fusion

25.5 Conclusion

References

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

26.1 Introduction

26.2 Used Signature Data

26.3 Image Types Used for Feature Extraction and Evaluation

26.4 Skills of Forgery Creation of Used Forgeries

26.5 Previous Work and Motivation for 3D RKI

26.6 3D Reference Knowledge of Signature

26.7 Ammar Matching Technique

26.8 Feature Extraction

26.9 Distance Measure and Verification

26.10 Experimental Results and Discussion

26.11 Limited Results are Shown and Discussed

26.12 AMT Features and Signature Recognition

26.13 AMT and Closely Related Works

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

26.15 Conclusions

References

27 Unified Entropy Theory and Maximum Discrimination on Pattern Recognition

27.1 Introduction

27.2 Unified Entropy Theory in Pattern Recognition

27.3 Mutual-Information—Discriminate Entropy in Pattern Recognition

27.4 Mutual Information Discrimination Analysis in Pattern Recognition

27.5 Maximum MI principle

27.6 Maximum MI Discriminate SubSpace Recognition in Handwritten Chinese Character Recognition

27.7 Conclusion

References

28 Fundamentals of Biometrics—Hand Written Signature and Iris

28.1 Prologue

28.2 Fundamentals of Handwritten Signature

28.3 Acquisition

28.4 Databases

28.5 Signature Analysers

28.6 Off-line Methods

28.7 On-line Methods

28.8 Fundamentals of Iris

28.9 Feature Extraction

28.10 Preprocessing

28.11 Iris Image Databases

28.12 Iris Analyzers

28.13 Conclusion

References

29 Recent Trends in Iris Recognition

29.1 Introduction

29.2 Basic Modules of Iris Recognition

29.3 Performance Measures

29.4 Limitations of Current Techniques

29.5 Future Scope

References

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

30.1 Introduction

30.2 Signature Data

30.3 ASV Systems Using Threshold-Based Decision

30.4 MSF and Its Performance

30.5 IFS and QP

30.6 Conclusion

References

31 Fourier Transform in Numeral Recognition and Signature Verification

31.1 Concepts of Digital Transforms

31.2 Orthonormal System of Trigonometric Functions

31.3 Introduction to Discrete Fourier Transform

31.4 Properties of DFT

31.5 DFT Calculation Problem

31.6 Description of a Numeral Through Fourier Coefficents

31.7 Numeral Recognition Through Fourier Transform

31.8 Signature Verification Systems Trough Fourier Analysis

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

References

Index