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Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition

Book Description

The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Preface
  7. Chapter 1: From Object Recognition to Object Localization
    1. ABSTRACT
    2. INTRODUCTION
    3. LOCAL APPEARANCE-BASED OBJECT RECOGNITION AND MULTI-CAMERA SYSTEMS
    4. OBJECTS’ POSE AND POSITION ESTIMATION IN THE 3D SPACE
    5. CONCLUSION AND FUTURE WORK
  8. Chapter 2: A Multi-Linear Statistical Method for Discriminant Analysis of 2D Frontal Face Images
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. Statistical Discriminant Method (SDM)
    5. Future Research Directions
    6. Conclusion
  9. Chapter 3: Orthogonal Image Moment Invariants
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND IN IMAGE MOMENTS
    4. 3. IMAGE MOMENTS
    5. 4. ORTHOGONAL IMAGE MOMENT INVARIANTS
    6. Future Research Directions
    7. Conclusion
  10. Chapter 4: Certain and Uncertain Triangulation in Multiple Camera Vision Systems via LMIs
    1. Abstract
    2. INTRODUCTION
    3. NOTATION AND PROBLEM FORMULATION
    4. PROPOSED TECHNIQUE
    5. RESULTS
    6. Future Directions
    7. Conclusion
  11. Chapter 5: Camera Calibration with 1D Objects
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. SINGLE CAMERA CALIBRATION
    5. 4. IMPROVEMENT OF THE METHOD
    6. 5. MULTIPLE CAMERA CALIBRATION
    7. 7. CONCLUSION
  12. Chapter 6: Object Segmentation Based on a Nonparametric Snake with Motion Prediction in Video
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. A Proposed Object Segmentation Method in Video
    5. FUTURE RESEARCH
    6. Conclusion
  13. Chapter 7: Analysis of Face Space for Recognition using Interval-Valued Subspace Technique
    1. Abstract
    2. INTRODUCTION
    3. CHALLENGES IN FACE RECOGNITION
    4. APPLICATIONS OF FACE RECOGNITION
    5. Appearance-Based Face Recognition Techniques
    6. Symbolic KFD Method for Face Recognition
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
  14. Chapter 8: Object Recognition with a Limited Database Using Shape Space Theory
    1. Abstract
    2. 1. INTRODUCTION
    3. 2. Background
    4. 3. THE SHAPE SPACE THEORY
    5. 4. AUGMENTING DATABASE CONTENT
    6. 5. OBJECT RECOGNITION BASED ON THE SHAPE SPACE THEORY
    7. 6. FUTURE RESEARCH DIRECTIONS
    8. 7. CONCLUSION
  15. Chapter 9: Efficient Iris Identification with Improved Segmentation Techniques
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. RELATED WORK
    4. 3. NEW AND IMPROVED IRIS RECOGNITION METHOD AND ITS MAJOR COMPONENTS
    5. 4. EXPERIMENTAL RESULTS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
  16. Chapter 10: Color Image Segmentation of Endoscopic and Microscopic Images for Abnormality Detection in Esophagus
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. DETECTION OF ABNORMAL REGION IN ENDOSCOPIC IMAGE
    4. 3. CELL NUCLEI SEGMENTATION IN MICROSCOPIC IMAGES OF SQUAMOUS CELL CARCINOMA
    5. 4. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
  17. Chapter 11: Adaptive Face Recognition of Partially Visible Faces
    1. Abstract
    2. 1. Introduction
    3. 2. Motivation
    4. 3. Background
    5. 4. Proposed System
    6. 5. Future Research Directions
    7. 6. CONCLUSION
  18. Chapter 12: Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. METHODOLOGY
    5. 4. RESULTS AND OBSERVATIONS
    6. 5. CONCLUSION
    7. FUTURE RESEARCH DIRECTIONS
  19. Chapter 13: Feature Set Reduction in Rotation Invariant CBIR Using Dual-Tree Complex Wavelet Transform
    1. ABSTRACT
    2. 1. CONTENT BASED IMAGE RETRIEVAL (CBIR) SYSTEM: AN OVERVIEW
    3. 2. REVIEW OF EXISTING WORKS
    4. 3. FEATURE EXTRACTION METHOD
    5. 4. PROPOSED REDUCTION IN FEATURE SET
    6. 5. INDEXING AND RETRIEVAL
    7. 6. EXPERIMENTAL RESULTS
    8. 7. COMPARISON OF PERFORMANCE WITH EXISTING METHODS
    9. 8. CONCLUSION
  20. Chapter 14: Devnagari Script Recognition
    1. Abstract
    2. Introduction
    3. Background
    4. LITERATURE SURVEY AND RELATED REFERENCES OF EXISTING TECHNIQUES FOR OCR
    5. PREPROCESSING AND FEATURE EXTRACTION: EXISTING METHODOLOGIES
    6. PRE-PROCESSING AND FEATURE EXTRACTION: MODIFICATIONS AND NEW ALGORITHMS FOR OCR
    7. Feature Extraction and Classification Module for Devnagari OCR
    8. EXPERIMENTATION, RESULTS AND OBSERVATIONS
    9. CONCLUSION AND FUTURE DIRECTIONS
  21. Chapter 15: Corner Detection Using Fuzzy Principles
    1. Abstract
    2. 1 INTRODUCTION
    3. 2 FUZZY RULE-BASED SYSTEM
    4. 3 EXPERIMENTAL RESULTS
    5. 4 PERFORMANCE COMPARISON
    6. 5 CONCLUSION
  22. Chapter 16: Eye Detection Using Color, Haar Features, and Efficient Support Vector Machine
    1. Abstract
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. OVERVIEW OF PROPOSED METHOD
    5. 4. EYE CANDIDATE SELECTION
    6. 5. DISCRIMINATORY IMAGE REPRESENTATIONS FOR EYES
    7. 6 EFFICIENT SUPPORT VECTION MACHINE (eSVM)
    8. 7. EXPERIMENTS
    9. 8 CONCLUSION AND FUTURE WORK
  23. Chapter 17: Emotion Recognition from Facial Expression and Electroencephalogram Signals
    1. Abstract
    2. INTRODUCTION
    3. MULTIMODAL EMOTION RECOGNITION
    4. Extraction of Facial Attributes
    5. Emotion Classification by Support Vector Machine
    6. EEG Based Emotion Recognition
    7. The Duffing Oscillator Dynamics
    8. Emotion Clustering Using Duffing Oscillator
    9. RELATIVE PERFORMANCE OF THE PROPOSED SCHEMES
    10. CONCLUSION
    11. ADDITIONAL READING
  24. Chapter 18: Detecting Eyes and Lips Using Neural Networks and SURF Features
    1. Abstract
    2. INTRODUCTION
    3. FACE DETECTION
    4. FACIAL FEATURES DETECTION
    5. EXPERIMENTAL RESULTS AND DISCUSSION
    6. CONCLUSION
  25. Chapter 19: Classification with Axis-Aligned Rectangular Boundaries
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. a proposed CLASSIFICATION METHOD
    5. FuTURE rESEARCH
    6. Conclusion
  26. Chapter 20: ICA as Pattern Recognition Technique for Gesture Identification
    1. Abstract
    2. INTRODUCTION
    3. related work
    4. Background
    5. MATERIALS AND Methods
    6. Results
    7. Discussions and Conclusion
    8. future directions
  27. Chapter 21: Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. Fuzzy models of multiple-criteria evaluation
    5. FuTURE rESEARCH dIRECTIONS
    6. Conclusion
  28. Chapter 22: Realizing Interval Type-2 Fuzzy Systems with Type-1 Fuzzy Systems
    1. Abstract
    2. INTRODUCTION
    3. General T2 FSs
    4. IT2 FSs and IT2 FLSs
    5. REALIZATION METHODOLOGY FOR IT2 FLS WITH T1 FLSs
    6. experiments and simulation results
    7. CONCLUSION AND FUTURE WORK
  29. Chapter 23: Comparative Analysis of Random Forests with Statistical and Machine Learning Methods in Predicting Fault-Prone Classes
    1. Abstract
    2. 1 INTRODUCTION
    3. 2 An Overview of Random Forest (RF) Algorithms
    4. 3 Empirical Evaluation
    5. 4 Research Methodology
    6. 5. Analysis Results
    7. 6 Conclusion
  30. Chapter 24: Neural Networks
    1. Abstract
    2. INTRODUCTION
    3. THE BIOLOGICAL NEURON: STRUCTURE AND OPERATION
    4. ARTIFICIAL NEURAL NETWORKS
    5. Artificial neural network architectures
    6. Advances in neural networking paradigm
    7. Application Perspectives
    8. Discussions and Conclusion
    9. Acknowledgment
  31. Chapter 25: A New Optimization Approach to Clustering Fuzzy Data for Type-2 Fuzzy System Modeling
    1. ABSTRACT
    2. INTRODUCTION
    3. FUZZY CLUSTER ANALYSIS
    4. FUZZY SIMILARITY MEASURE
    5. THE MODIFIED FCM WITH FUZZY NUMBERS
    6. CLUSTER VALIDITY INDEX
    7. IMPLEMENTATION
    8. CONCLUSION
  32. Chapter 26: Estimation of MIMO Wireless Channels Using Artificial Neural Networks
    1. Abstract
    2. 1. INTRODUCTION
    3. 2. Characteristics of multipath channel
    4. 3. MIMO Channel Capacity and modelling fading characteristics
    5. 4. Basic Considerations of MIMO-OFDM System
    6. 5. Literature Survey
    7. 6 Motivation
    8. 7 Necessity of ANN based methods
    9. 7.3 Application of Error Backpropagation for MlP Training
    10. 8 Experimental Results and Discussion
    11. 9 Temporal-MLP architecture for MIMO channel modeling
    12. 10 Conclusion
  33. Chapter 27: A Novel 3D Approach for Patient Schedule Using Multi-Agent Coordination
    1. Abstract
    2. INTRODUCTION
    3. Problem Domain
    4. Related Work
    5. A Novel 3D Patient Scheduling
    6. Implementation
    7. Future Work AND Research Directions
    8. Conclusion
  34. Chapter 28: A Fuzzy Approach to Disaster Modeling
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. Preliminaries
    5. Problem specification
    6. Mathematical model
    7. NUmerical example
    8. FuTURE rESEARCH dIRECTIONS
    9. Conclusion
  35. Chapter 29: Fuzzy Cognitive Map Reasoning Mechanism for Handling Uncertainty and Missing Data
    1. Abstract
    2. INTRODUCTION
    3. FUZZY COGNITIVE MAPS
    4. Fuzzy Cognitive Map Modeling Approach to Assess Pulmonary Risk
    5. Results and Discussion
    6. Future Research Directions
    7. Conclusion
  36. Chapter 30: On the Use of Fuzzy Logic in Electronic Marketplaces
    1. Abstract
    2. INTRODUCTION
    3. Background
    4. fuzzy logic in e-markets
    5. methodologies for building fuzzy systems
    6. FuTURE rESEARCH dIRECTIONS
    7. Conclusion
  37. Chapter 31: A Neuro-Fuzzy Expert System Trained by Particle Swarm Optimization for Stock Price Prediction
    1. ABSTRACT
    2. INTRODUCTION
    3. Background
    4. ANFIS Structure
    5. Learning algorithms
    6. Particle Swarm Optimization (PSO)
    7. Designing a systematic neuro-fuzzy expert system
    8. Fuzzy clustering of the output
    9. Input selection
    10. Input membership assignment
    11. Tuning the parameters of membership function of input and output variables
    12. application of the proposed neuro-fuzzy expert system model FOR stock price prediction
    13. Multiple Regressions
    14. Sugeno-Yasukawa Approach
    15. ANFIS
    16. CONCLUSION AND FUTURE WORKS
  38. Chapter 32: Hand Tremor Prediction and Classification Using Electromyogram Signals to Control Neuro-Motor Instability
    1. ABSTRACT
    2. INTRODUCTION
    3. PREVIEW OF LITERATURE
    4. BIOLOGICAL BASIS OF CONSIDERING EMG SIGNALS FOR TREMOR COMPENSATION
    5. PRINCIPLES AND FUNCTIONAL ARCHITECTURE OF THE TREMOR PREDICTION SYSTEM
    6. TREMOR PREDICTION BY NEURAL NET
    7. TREMOR PREDICTION BY EXTENDED KALMAN FILTER
    8. EMBEDDED REALIZATION OF THE TREMOR CONTROLLER
    9. EXPERIMENTS AND RESULTS
    10. CONCLUSION
    11. APPENDIX: FURTHER READINGS
  39. Compilation of References
  40. About the Contributors