前辅文
Part I: 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
Part II: 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
Part III: 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
Part IV: 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 Transition 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
