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Multi-Core Computer Vision and Image Processing for Intelligent Applications

Book Description

A multicore platform uses distributed or parallel computing in a single computer, and this can be used to assist image processing algorithms in reducing computational complexities. By implementing this novel approach, the performance of imaging, video, and vision algorithms would improve, leading the way for cost-effective devices like intelligent surveillance cameras. Multi-Core Computer Vision and Image Processing for Intelligent Applications is an essential publication outlining the future research opportunities and emerging technologies in the field of image processing, and the ways multi-core processing can further the field. This publication is ideal for policy makers, researchers, technology developers, and students of IT.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board
  6. Preface
    1. AN OVERVIEW OF THE BOOK
    2. TARGET AUDIENCE
    3. ABOUT THE CHAPTERS
    4. CONCLUSION
  7. Chapter 1: FPGA-Based Re-Configurable Architecture for Window-Based Image Processing
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. RELATED WORK AND MOTIVATION
    4. 3. MEDIAN BASED FILTERING ALGORITHMS
    5. 4. HARDWARE ARCHITECTURE
    6. 5. IMPLEMENTATION ISSUES OF HARDWARE ARCHITECTURE
    7. 6. RESULTS AND ITS ANALYSIS
    8. 7. CONCLUSION
    9. REFERENCES
  8. Chapter 2: Mobile Platform Challenges in Interactive Computer Vision
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. COMPUTATIONAL PERFORMANCE: LATENCY AND THROUGHPUT
    4. 3. ENERGY EFFICIENCY
    5. 4. ASYMMETRIC MULTIPROCESSING FOR VISION-BASED INTERACTIVITY
    6. 5. MOBILE PLATFORM AS A SET OF HETEROGENEOUS COMPUTATIONAL DEVICES
    7. 6. DISCUSSION
    8. REFERENCES
  9. Chapter 3: Fish Tracking with Computer Vision Techniques
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PROPOSED TECHNIQUE
    4. 3. EXPERIMENTAL RESULTS
    5. 4. CONCLUSION
    6. REFERENCES
  10. Chapter 4: Computer Vision Based Classification on Commercial Videos
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FRAMEWORK
    4. 3. CLASSIFIERS
    5. 4. PROPOSED TECHNIQUES
    6. 5. EXPERIMENTAL ANALYSIS
    7. 6. RESULTS AND DISCUSSIONS
    8. 7. MULTICORE IMPLEMENTATION OF C4.5 ALGORITHM
    9. 8. CONCLUSION
    10. REFERENCES
  11. Chapter 5: Creating Sound Glyph Database for Video Subtitling
    1. ABSTRACT
    2. INTRODUCTION
    3. BUILDING A SOUND-GLYPH DATABASE
    4. MULTIRESOLUTION: MULTICORE APPROACH TO BUILDING SOUND-GLYPH DATABASE
    5. EVALUATION OF THE MULTIRESOLUTION AND MULTI-CORE APPROACH
    6. CONCLUSION
    7. REFERENCES
  12. Chapter 6: Parallel Computing in Face Image Retrieval
    1. ABSTRACT
    2. INTRODUCTION
    3. FUTURE RESEARCH AND DEVELOPMENT
    4. CONCLUSION
    5. ACKNOWLEDGMENT
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  13. Chapter 7: Fish Monitoring, Sizing, and Detection Using Stereovision, Laser Technology, and Computer Vision
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FISH MONITORING AND SIZING USING STEREOVISION AND COMPUTER VISION
    4. 3. FISH DETECTION IN SLOT FISHWAYS USING LASER TECHNOLOGY AND COMPUTER VISION
    5. 4. RESULTS
    6. 5. CONCLUSION
    7. ACKNOWLEDGMENT
    8. REFERENCES
  14. Chapter 8: Controlling Prosthetic Limb Movements Using EEG Signals
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. DATA ACQUISITION AND SYSTEM ARCHITECTURE
    4. 3. FEATURES SUGGESTED BY C4.5 DECISION TREE ALGORITHM
    5. 4. SUMMARY
    6. 5. APPLICATION OF DECISION TREE (C4.5 ALGORITHM)
    7. 6. MULTICORE IMPLEMENTATION OF C4.5 ALGORITHM
    8. 7. CONCLUSION
    9. REFERENCES
  15. Chapter 9: A Technical Assessment on License Plate Detection System
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. OBJECT DETECTION
    5. CASE STUDY
    6. SOLUTIONS AND RECOMMENDATIONS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  16. Compilation of References
  17. About the Contributors