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Intelligent Analysis of Multimedia Information

Book Description

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Dedication
  6. Editorial Advisory Board and List of Contributors
    1. Editorial Advisory Board
  7. Preface
  8. Chapter 1: Foundations of Multimedia Information Processing
    1. ABSTRACT
    2. BACKGROUND
    3. INTRODUCTION
    4. 1. IMAGE SCENE
    5. 2. VIDEO SCENE
    6. 3. SHOTS
    7. 4. FRAMES
    8. 5. HYPERMEDIA
    9. 6. SEGMENTATION
    10. CONCLUSION
    11. REFERENCES
  9. Chapter 2: Theoretical Concepts and Technical Aspects on Image Segmentation
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. IMAGE SEGMENTATION
    5. MODEL-BASED SEGMENTATION
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  10. Chapter 3: Feature Extraction
    1. ABSTRACT
    2. BACKGROUND
    3. INTRODUCTION
    4. 1. GENERAL FEATURE EXTRACTION TECHNIQUES
    5. 2. MOTION ESTIMATION
    6. 3. SHOT
    7. 4 COLOR ANALYSIS
    8. 5. DYNAMIC CONTENT GESTURE ANALYSIS
    9. 6. AUDIO VIDEO ANALYSIS
    10. 7. SPEECH TRANSCRIPTS
    11. 8. OBJECT RECOGNITION
    12. 9. POPULAR IMAGE RETRIEVAL TECHNIQUES
    13. CONCLUSION
    14. REFERENCES
  11. Chapter 4: Multilevel Image Segmentation Using Modified Particle Swarm Optimization
    1. ABSTRACT
    2. INTRODUCTION
    3. LITERATURE REVIEW
    4. PREREQUISITE TECHNOLOGIES
    5. MODIFIED PARTICLE SWARM OPTIMIZATION
    6. PROPOSED METHODOLOGY
    7. Experimental results and analysis
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  12. Chapter 5: Retrieval of Multimedia Information Using Content-Based Image Retrieval (CBIR) Techniques
    1. ABSTRACT
    2. INTRODUCTION
    3. LITERATURE REVIEWS
    4. MAIN FOCUS OF THE CHAPTER
    5. FEATURE EXTRACTION OR VISUAL CONTENTS
    6. MULTIDIMENSIONAL INDEXING
    7. RETRIEVAL METHOD
    8. IMAGE RETRIEVAL (IR)
    9. SEMANTIC GAP
    10. SENSORY GAP
    11. QUERY TECHNIQUES FOR CBIR
    12. IMAGE RETRIEVAL SYSTEM
    13. APPLICATIONS OF CONTENT-BASED IMAGE RETRIEVAL:
    14. PERFORMANCE EVALUATION
    15. FUTURE RESEARCH DIRECTIONS
    16. CHALLENGES OF CONTENT-BASED IMAGE RETRIEVAL SYSTEM
    17. CONCLUSION
    18. REFERENCES
    19. KEY TERMS AND DEFINITIONS
  13. Chapter 6: Biomedical Image Processing and Analysis
    1. ABSTRACT
    2. INTRODUCTION
    3. FUTURE RESEARCH DIRECTIONS
    4. REFERENCES
    5. KEY TERMS AND DEFINITIONS
  14. Chapter 7: Cellular Automata Algorithms for Digital Image Processing
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. TESTING AND RESULTS
    5. FUTURE RESEARCH DIRECTIONS
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  15. Chapter 8: Indian River Watershed Image Analysis Using Fuzzy-CA Hybrid Approach
    1. ABSTRACT
    2. INTRODUCTION
    3. HYBRID FUZZY-CA CLUSTERING ALGORITHM
    4. CELLULAR AUTOMATA BASED NEIGHBORHOOD PRIORITY CORRECTION METHOD
    5. APPLICATION TO PIXEL CLASSIFICATION
    6. QUANTITATIVE ANALYSIS
    7. STATISTICAL ANALYSIS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  16. Chapter 9: A Fuzzy Relational Classifier Based Image Quality Assessment Method
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FEATURE SELECTION
    4. 3. ENTROPY OF FEATURES
    5. 4. FUZZY RELATIONAL CLASSIFICATION
    6. 5. IMAGE PARTITIONING
    7. 6. CLASS MEMBERSHIP GENERATION
    8. 8. RESULTS OF FUZZY RELATIONAL CLASSIFIER
    9. 9. SUMMARY
    10. REFERENCES
  17. Chapter 10: Data Compression as a Base for eHealth Interoperability
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. CONSTRUCTION OF COMPRESSION METHODS
    5. SOLUTIONS AND RECOMMENDATIONS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  18. Chapter 11: Detection of Gradual Transition in Videos
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. TYPES OF GRADUAL TRANSITIONS
    5. 4. ISSUES AND CHALLENGES OF GRADUAL TRANSITIONS
    6. 5. PARAMETERS FOR DETECTING GRADUAL TRANSITIONS
    7. 6. PITFALLS OF PARAMETERS IN DETECTING GRADUAL TRANSITIONS
    8. 7. PROPOSED METHOD
    9. 8. EXPERIMENTAL RESULTS AND ANALYSIS
    10. 9. CONCLUSION
    11. REFERENCES
  19. Chapter 12: Time-Slot Based Intelligent Music Recommender in Indian Music
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. HISTORICAL BACKGROUNDS
    4. 3. MOBILE CLOUD COMPUTING
    5. 4. MUSIC RECOMMENDATION SYSTEM
    6. 5. TIME SLOT BASED MUSIC RECOMMENDATION SYSTEM
    7. 6. ANALYSIS AND DISCUSSION
    8. 7. FUTURE CHALLENGES
    9. 8. CONCLUSION
    10. ACKNOWLEDGMENT
    11. REFERENCES
  20. Chapter 13: Content Coverage and Redundancy Removal in Video Summarization
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BASIC CONCEPTS
    4. 3. REVIEW OF VIDEO SUMMARIZATION TECHNIQUES
    5. 4. OBJECTIVES OF VIDEO SUMMARIZATION
    6. 5. PROCESSING STEPS OF VIDEO FOR SUMMARIZATION, INDEXING AND RETRIEVAL
    7. 6. ASPECTS OF VIDEO SUMMARIZATION
    8. 7. CONCLUSION
    9. REFERENCES
  21. Chapter 14: Compressive Sensing for Biometric System
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. LITERATURE REVIEW
    4. 3. OVERVIEW ON COMPRESSIV SENSING (CS) THEORY
    5. 4. APPLICATION OF CS THEORY FOR BIOMETRIC SYSTEM
    6. 5. CONCLUSION AND FUTURE WORK
    7. REFERENCES
  22. Chapter 15: Integration of Different Analytical Concepts on Multimedia Contents in Service of Intelligent Knowledge Extraction
    1. ABSTRACT
    2. INTRODUCTION
    3. POTENTIAL OF MULTIMEDIA DATA IN MARKETING
    4. MARKET RESEARCH MODEL BASED ON MULTIMEDIAL DATA
    5. CASE STUDY
    6. CONCLUSION
    7. FUTURE RESEARCH DIRECTIONS
    8. DISCUSSION
    9. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  23. Chapter 16: Digital Watermarking
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BRIEF LITERATURE REVIEW OF WATERMARKING
    4. 3. COMPARISON OF WATERMARKING TECHNIQUE WITH THE OTHER DATA HIDING TECHNIQUES
    5. 4. DATA USED FOR IMPLEMENTATION OF WATERMARKING TECHNIQUES
    6. 5. DIGITAL WATERMARKING TECHNIQUES IN SPATIAL DOMAIN
    7. 6. DIGITAL WATERMARKING TECHNIQUES IN TRANSFORM DOMAIN
    8. 7. ADVANCE DIGITAL WATERMARKING TECHNIQUES
    9. 8. CONCLUSION AND FUTURE WORK
    10. REFERENCES
  24. Compilation of References
  25. About the Contributors