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Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing

Book Description

Whether an old photograph or a single video frame, there is a wealth of data hidden in a picture. Image processing and pattern analysis play a vital role in engineering science and can be applied in diverse areas to solve existing and practical problems. The Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing discusses the advances of image processing and pattern analysis and addresses how new innovations will cater to the demands of daily life. This handbook provides the resources necessary for technology developers, scientists, and policymakers to adopt and implement new inventions across the globe. The chapters presented in this publication encompass various aspects of recent image processing and pattern analysis innovations including, but not limited to, mobile image tracking, motion picture analysis, pattern classification, multisensory data fusion, 3D imaging, supporting routing protocols, brain computer interfaces, image restoration, and medical imaging.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board
  6. Foreword
  7. Preface
    1. ORGANIZATION OF THE BOOK
  8. Acknowledgment
  9. Section 1: Image Processing and Computer Vision
    1. Chapter 1: Image Data Mining Based on Wavelet Transform for Visualization of the Unique Characteristics of Image Data
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. A RATIONALE OF IMAGE DATA MINING
      4. 3. WAVELET TRANSFORM BASED IMAGE DATA MINING
      5. 4. ANNOTATING THE IMAGE UNIQUE FEATURE MINING AND VISUALIZATION
      6. 5. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
      10. ENDNOTES
    2. Chapter 2: Total Variation Applications in Computer Vision
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. APPLICATIONS OF TV-NORM IN COMPUTER VISION
      5. 4. FUTURE RESEARCH DIRECTIONS
      6. 5. CONCLUSION
      7. REFERENCES
      8. ADDITIONAL READING
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 3: Vision Enhancement in Bad Weather
      1. ABSTRACT
      2. INTRODUCTION
      3. BAD WEATHER: PARTICLES AROUND US
      4. CHALLENGES AND FRAMEWORK FOR VISION ENHANCEMENT
      5. RESEARCH AND IMPROVEMENTS ON DE-WEATHERING TECHNIQUES
      6. CLASSIFICATION OF FOG
      7. SIMULATION ANALYSIS AND DISCUSSION
      8. CONCLUSION AND FUTURE DIRECTION
      9. REFERENCES
    4. Chapter 4: Collective Event Detection by a Distributed Low-Cost Smart Camera Network
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. EXPERIMENTS AND RESULTS
      5. CONCLUSION
      6. REFERENCES
      7. KEY TERMS AND DEFINITIONS
    5. Chapter 5: Impulse Noise Filtering
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. VARIANTS OF IMPULSE NOISE
      4. 3. MEDIAN FILTER AS A TOOL OF IMPULSE NOISE REMOVAL
      5. 4. RECENT TRENDS TOWARDS THE ELIMINATION OF IMPULSE NOISE
      6. 5. COMPARATIVE ANALYSIS AMONGST DIFFERENT APPROACHES
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    6. Chapter 6: Utilizing Image Color Channels for High Payload Embedding
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. STEGO METHOD
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    7. Chapter 7: Anomaly Detection in Hyperspectral Imagery
      1. ABSTRACT
      2. INTRODUCTION
      3. ANOMALY DETECTION IN HYPERSPECTRAL IMAGERY
      4. DISCUSSION AND FUTURE RESEARCH DIRECTIONS
      5. CONCLUSION
      6. REFERENCES
      7. KEY TERMS AND DEFINITIONS
    8. Chapter 8: Cloud-Based Image Fusion Using Guided Filtering
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. IMAGE IN CLOUD RESOURCES
      5. CLOUD BASED IMAGE TRANSFORMATION
      6. IMAGE FUSION
      7. GUIDED FILTERING: A METHOD OF IMAGE FUSION
      8. CLOUD BASED IMAGE FUSION
      9. SCALE INVARIENT FEATURE DESCRIPTOR (SIFT)
      10. SCALE SPACE EXTREMA DETECTION
      11. KEYPOINTS LOCALIZATION
      12. ORIENTATION ASSIGNMENT
      13. KEYPOINTS DESCRIPTOR EXTRACTION
      14. IMAGE FUSION WITH GUIDED FILTERING
      15. FRAMEWORK
      16. IMPLEMENTATION
      17. CONCLUSION
      18. FUTURE WORK
      19. SUMMARY
      20. REFERENCES
      21. KEY TERMS AND DEFINITIONS
  10. Section 2: Pattern Recognition, Watermarking and Face Recognition
    1. Chapter 9: Determination of Stability of Rock Slope Using Intelligent Pattern Recognition Techniques
      1. ABSTRACT
      2. INTRODUCTION
      3. EXTREME LEARNING MACHINE
      4. MOORE PENROSE GENERALIZED THEORY
      5. MINIMUM NORM LEAST-SQUARES SOLUTION OF GENERAL LINEAR SYSYTEM
      6. EXTREME LEARNING MACHINE
      7. APPROXIMATION PROBLEM OF SLFNs
      8. GRADIENT-BASED LEARNING ALGORITHMS
      9. MINIMUM NORM LEAST SQUARES SOLUTION OF SLFN
      10. LEARNING ALGORITHM FOR SLFNs
      11. MINIMAX PROBABILITY MACHINE CLASSIFICATION
      12. DEVELOPMENT OF MODEL
      13. RESULTS AND DISCUSSIONS
      14. CONCLUSION
      15. REFERENCES
      16. KEY TERMS AND DEFINITIONS
    2. Chapter 10: 3D Image Acquisition and Analysis of Range Face Images for Registration and Recognition
      1. ABSTRACT
      2. INTRODUCTION
      3. 3D IMAGE ACQUISITION TECHNIQUES
      4. FILE FORMATS OF 3D IMAGES
      5. VISUALIZATION 3D FACE IMAGE
      6. 3D MESH VIEWING TECHNIQUE
      7. ANALYSIS OF 3D FACE IMAGES FROM RANGE IMAGE
      8. HISTOGRAM EQUALIZATION
      9. CONTRAST STRETCHING
      10. LITERATURE SURVEY AND DIFFERENT METHODOLOGIES
      11. LANDMARK DETECTION AND REGISTRATION OF 3D FACE IMAGES
      12. CONCLUSION
      13. ACKNOWLEDGMENT
      14. REFERENCES
      15. KEY TERMS AND DEFINITIONS
    3. Chapter 11: Face Recognition in Unconstrained Environment
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. CHALLENGES IN FACE RECOGNITION
      4. 3. WHY FACE RECOGNITION?
      5. 4. FACE RECOGNITION APPROACHES
      6. 5. EXPERIMENTAL RESULT AND DISCUSSION
      7. 6. CONCLUSION AND FUTURE DIRECTION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    4. Chapter 12: Intelligence-Based Adaptive Digital Watermarking for Images in Wavelet Transform Domain
      1. ABSTRACT
      2. INTRODUCTION
      3. BASICS OF DIGITAL WATERMARKING
      4. DIGITAL WATERMARKING SCHEMES IN TRANSFORM DOMAIN
      5. COMPUTATIONAL INTELLIGENCE AND WATERMARKING SCHEMES
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    5. Chapter 13: Feature Extraction Techniques
      1. ABSTRACT
      2. INTRODUCTION
      3. LOW-LEVEL FEATURE EXTRACTION
      4. HIGH-LEVEL FEATURE EXTRACTION
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
  11. Section 3: Bio Imaging and Applications
    1. Chapter 14: Metal Artifact Reduction
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. EXISTING MAR METHODS
      4. 3. PROPOSED METHODOLOGY
      5. 4. RESULTS AND DISCUSSION
      6. CONCLUSION AND FUTURE SCOPE
      7. REFERENCES
    2. Chapter 15: Improved Lymphocyte Image Segmentation Using Near Sets for ALL Detection
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. MATERIAL AND METHODS
      4. 3. CLUSTERING BASED IMAGE SEGMENTATION
      5. 4. PROPOSED LEUKOCYTE SEGMENTATION
      6. 5. RESULTS AND ANALYSIS
      7. 6. CONCLUSION AND FUTURE WORK
      8. ACKNOWLEDGMENT
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    3. Chapter 16: Biometric Identification System Using Neuro and Fuzzy Computational Approaches
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND LITERATURE REVIEW
      4. MOTIVATION
      5. BASIC THEORETICAL CONSIDERATIONS
      6. PREPROCESSING AND FEATURE EXTRACTION OF FINGERPRINT AND RETINA
      7. ENHANCEMENT OPERATIONS
      8. MORPHOLOGICAL OPERATIONS
      9. FEATURE EXTRACTION
      10. RETINA AND FINGERPRINT RECOGNITION USING ANFIS FOR BIOMETRIC IDENTIFICATION
      11. EXPERIMENTAL DETAILS AND RESULTS
      12. CONCLUSION AND FUTURE DIRECTION
      13. REFERENCES
      14. KEY TERMS AND DEFINITIONS
    4. Chapter 17: A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE SURVEY
      4. 3. SYSTEM ARCHITECTURE
      5. 4. PROPOSED ALGORITHM OF SYSTEM
      6. 5. FUZZY AS A CLASSIFIER
      7. 6. RESULT AND DISCUSSION
      8. 7. CONCLUSION
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    5. Chapter 18: Application of Charge System Search Algorithm for Data Clustering
      1. ABSTRACT
      2. INTRODUCTION
      3. CSS ALGORITHM FOR CLUSTERING
      4. CLUSTERING ALGORITHMS
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    6. Chapter 19: Learning Aided Digital Image Compression Technique for Medical Application
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. LITERATURE REVIEW
      5. CONTRIBUTION
      6. ORGANIZATION OF THE CHAPTER
      7. THEORETICAL CONSIDERATIONS
      8. PROPOSED APPROACH
      9. SUMMARY
      10. CONCLUSION
      11. LIMITATION
      12. FUTURE DIRECTION
      13. REFERENCES
      14. KEY TERMS AND DEFINITIONS
  12. Compilation of References
  13. About the Contributors