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Emerging Technologies in Intelligent Applications for Image and Video Processing

Book Description

Image and Video Processing is an active area of research due to its potential applications for solving real-world problems. Integrating computational intelligence to analyze and interpret information from image and video technologies is an essential step to processing and applying multimedia data. Emerging Technologies in Intelligent Applications for Image and Video Processing presents the most current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. Featuring insight from researchers from around the world, this publication is designed for use by engineers, IT specialists, researchers, and graduate level students.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Dedication
  6. Editorial Advisory Board
  7. Preface
  8. Acknowledgment
  9. Section 1: Image and Video Enhancement, Restoration, and Segmentations
    1. Chapter 1: Image and Video Restoration and Enhancement via Sparse Representation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. IMAGE/VIDEO DENOISING VIA SPARSE REPRESENTATION
      5. IMAGE/VIDEO SUPER-RESOLUTION VIA SPARSE REPRESENTATION
      6. COMPARATIVE STUDIES AND EVALUATION RESULTS
      7. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
    2. Chapter 2: An Efficient Method for Optimizing Segmentation Parameters
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. PROPOSED PARAMETER OPTIMIZATION METHOD
      5. 4. EXPERIMENTAL RESULTS
      6. 5. FUTURE RESEARCH DIRECTIONS
      7. 6. CONCLUSION
      8. REFERENCES
    3. Chapter 3: Study of Noise Removal Techniques for Digital Images
      1. ABSTRACT
      2. INTRODUCTION
      3. TYPES OF IMAGE
      4. IMAGE FILE FORMATS
      5. TYPES OF NOISE
      6. IMAGE DENOISING SCHEMES
      7. PERFORMANCE MEASURES
      8. IMPLEMENTATION OF VARIOUS DENOISING ALGORITHMS
      9. RELATED WORKS
      10. DISCUSSION
      11. DIRECTIONS FOR FUTURE RESEARCH
      12. REFERENCES
    4. Chapter 4: Incorporation of Depth in Two Dimensional Video Captures
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BASIC THEORETICAL ASPECTS
      4. 3. REVIEW OF RECENT METHODS OF 2D TO 3D VIDEO CONVERSION
      5. 4. GENERIC SYSTEM FOR INCORPORATION OF DEPTH INFORMATION IN 2D VIDEO
      6. 5. CONCLUSION
      7. REFERENCES
  10. Section 2: Image and Video Compression, Indexing, and Retrieval
    1. Chapter 5: Wavelets with Application in Image Compression
      1. ABSTRACT
      2. INTRODUCTION
      3. PRELIMINARIES
      4. BACKGROUND
      5. SCALING AND WAVELET FUNCTIONS
      6. WAVELET TRANSFORM ALGORITHM FOR DIGITAL IMAGE
      7. IMAGE COMPRESSION
      8. APPLICATION OF WAVELETS IN IMAGE COMPRESSION
      9. SOME MATLAB COMMANDS AND USER DEFINED FUNCTIONS
      10. FUTURE RESEARCH DIRECTIONS
      11. CONCLUSION
      12. REFERENCES
      13. KEY TERMS AND DEFINITIONS
    2. Chapter 6: An Efficient Algorithm for Fast Block Motion Estimation in High Efficiency Video Coding
      1. ABSTRACT
      2. INTRODUCTION
      3. EXISTING METHODS
      4. EXPERIMENTAL RESULTS AND DISCUSSION
      5. CONCLUSION
      6. REFERENCES
    3. Chapter 7: Multi-Modal Fusion Schemes for Image Retrieval Systems to Bridge the Semantic Gap
      1. ABSTRACT
      2. INTRODUCTION
      3. OVERVIEW
      4. VARIOUS METHODOLOGIES FOR FUSION OF CONTENT AND TEXT FOR IMAGE RETRIEVAL
      5. EXPERIMENTAL RESULTS AND DISCUSSIONS
      6. CONCLUSION
      7. FUTURE PERSPECTIVES
      8. REFERENCES
    4. Chapter 8: Indexing of Image Features Using Quadtree
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. PROPOSED WORK
      5. COLOR COHERENCE VECTOR (CCV)
      6. SEGMENTATION BASED FRACTAL TEXTURE ANALYSIS
      7. FOURIER DESCRIPTORS
      8. COMBINING THE FEATURES
      9. INDEXING
      10. EXPERIMENTAL RESULTS
      11. CONCLUSION
      12. REFERENCES
  11. Section 3: Image and Video Processing in Public Safety
    1. Chapter 9: Early Recognition of Suspicious Activity for Crime Prevention
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. VISUAL INFORMATION REPRESENTATION AND ACTIVITY RECOGNITION APPROACHES
      4. HUMAN ACTION RECOGNITION FRAMEWORK - OVERVIEW
      5. ACTION PREDICTION PROBLEM
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. ACKNOWLEDGMENT
      9. REFERENCES
    2. Chapter 10: Iris Identification System
      1. ABSTRACT
      2. INTRODUCTION
      3. OVERVIEW OF BIOMETRICS
      4. ANATOMY OF HUMAN EYE AND IRIS
      5. IRIS RECOGNITION SYSTEM
      6. IRIS FEATURE EXTRACTION
      7. RECENT RESEARCH IN IRIS
      8. IRIS DATABASES
      9. PERFORMANCE METRICS
      10. CONCLUSION
      11. REFERENCES
    3. Chapter 11: Object Classification and Tracking in Real Time
      1. ABSTRACT
      2. 1. OBJECT DETECTION
      3. 2. FEATURE EXTRACTION AND REPRESENTATION
      4. 3. SUPERVISED LEARNING BASED DETECTION/ SEGMENTATION (CLASSIFICATION)
      5. 4. OBJECT TRACKING
      6. CONCLUSION
      7. REFERENCES
    4. Chapter 12: Gait Based Biometric Authentication System with Reduced Search Space
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROPOSED APPROACH
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
    5. Chapter 13: Lung Disease Classification by Novel Shape-Based Feature Extraction and New Hybrid Genetic Approach
      1. ABSTRACT
      2. INTRODUCTION
      3. OBJECTIVE OF THE CHAPTER
      4. BACKGROUND
      5. METHODOLOGY
      6. DATA COLLECTION
      7. PREPROCESSING TECHNIQUES
      8. GRAY SCALE CONVERSION
      9. MEDIAN FILTER
      10. MORPHOLOGICAL SMOOTHENING
      11. FEATURE EXTRACTION METHODS
      12. MOMENT INVARIANTS
      13. PROPOSED MULTISCALE FILTER BASED METHOD
      14. PROPOSED M FEATURE EXTRACTION METHOD
      15. FEATURE SELECTION
      16. WRAPPER METHODS
      17. HYBRID GENETIC ALGORITHM
      18. PROPOSED HYBRID GENETIC ALGORITHM FEATURE SELECTION
      19. WORKING OF THE PROPOSED HYBRID GENETIC ALGORITHM
      20. ADVANTAGES OF THE PROPOSED WORK
      21. CLASSIFIERS
      22. SVM CLASSIFIER
      23. MULTILAYER PERCEPTRON NEURAL NETWORK CLASSIFIER
      24. BAYES NET CLASSIFIER
      25. RESULTS AND DISCUSSIONS
      26. PERFORMANCE MEASURES
      27. CONCLUSION
      28. FUTURE RESEARCH DIRECTIONS
      29. REFERENCES
    6. Chapter 14: Fingerprint Iris Palmprint Multimodal Biometric Watermarking System Using Genetic Algorithm-Based Bacterial Foraging Optimization Algorithm
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. PROPOSED WORK
      5. BIOMETRIC MODALITY EXTRACTION
      6. MULTIMODAL BIOMETRIC SYSTEMS
      7. PERFORMANCE METRICS USED
      8. INTRODUCTION TO WATERMARKING
      9. PERFORMANCE METRICS
      10. CONCLUSION
      11. FUTURE RESEARCH DIRECTIONS
      12. REFERENCES
  12. Section 4: Image and Video Classification, Clustering, and Applications
    1. Chapter 15: Color Features and Color Spaces Applications to the Automatic Image Annotation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. COLOR FEATURES
      5. COLOR SPACES
      6. SOLUTIONS AND RECOMMENDATIONS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION AND DISCUSSION
      9. NOMENCLATURE
      10. REFERENCES
      11. ADDITIONAL READING
      12. KEY TERMS AND DEFINITIONS
    2. Chapter 16: Biomedical Imaging Techniques
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. IMAGING TECHNIQUES
      5. OTHER IMAGING TECHNIQUES
      6. NEED FOR SEVERAL IMAGING MODALITIES
      7. IMAGE QUALITY, IMAGE PROCESSING, AND VISUALIZATION OF IMAGES
      8. RADIATION EXPOSURE AND RADIATION PROTECTION IN MEDICAL IMAGING
      9. GENERAL APPLICATIONS OF MEDICAL IMAGING
      10. FUTURE ASPECTS OF MEDICAL IMAGING
      11. CONCLUSION
      12. REFERENCES
      13. KEY TERMS AND DEFINITIONS
    3. Chapter 17: A New EYENET Model for Diagnosis of Age-Related Macular Degeneration
      1. ABSTRACT
      2. INTRODUCTION
      3. MAIN FOCUS OF THE CHAPTER
      4. SOLUTIONS AND RECOMMENDATIONS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
    4. Chapter 18: Automatic Detection and Classification of Ischemic Stroke Using K-Means Clustering and Texture Features
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROPOSED APPROACH FOR ISCHEMIC STROKE
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
  13. Compilation of References
  14. About the Contributors