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Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies

Book Description

The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies features timely and informative research on the design and development of computer vision and image processing applications in intelligent agents as well as in multimedia technologies. Covering a diverse set of research in these areas, this publication is ideally designed for use by academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Preface
    1. INTRODUCTION
    2. COMPUTER VISION
    3. IMAGE PROCESSING
    4. LATEST ADVANCES
    5. CONCLUSION
    6. REFERENCES
  6. Chapter 1: Evaluating an Evolutionary Particle Swarm Optimization for Fast Fuzzy C-Means Clustering on Liver CT Images
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FUZZY C-MEANS CLUSTERING
    4. 3. PARTICLE SWARM OPTIMIZATION
    5. 4. FRACTIONAL ORDER DARWINIAN PSO
    6. 5. PROPOSED APPROACH
    7. 6. ABDOMINAL CT DATA COLLECTION
    8. EXPERIMENTAL RESULTS AND DISCUSSION
    9. 8. CONCLUSION
    10. REFERENCES
    11. KEY TERMS AND DEFINITIONS
    12. ENDNOTES
  7. Chapter 2: Automatic Mammographic Parenchyma Classification According to BIRADS Dictionary
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PREVIOUS WORK
    4. 3. MATERIALS AND METHODS
    5. 4. PROPOSED SYSTEM
    6. 5. EXPERIMENTAL RESULTS AND DISCUSSION
    7. 6. CONCLUSION AND FEATURE WORK
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  8. Chapter 3: Statistical Features-Based Diagnosis of Alzheimer's Disease using MRI
    1. ABSTRACT
    2. INTRODUCTION
    3. FEATURE EXTRACTION METHODS
    4. THE PROPOSED METHOD
    5. EXPERIMENTAL SETUP AND RESULTS
    6. CONCLUSION AND FUTURE WORK
    7. REFERENCES
    8. KEY TERMS AND DEFINITIONS
  9. Chapter 4: Use of Bi-Camera and Fusion of Pairwise Real Time Citrus Fruit Image for Classification Application
    1. ABSTRACT
    2. INTRODUCTION
    3. MATERIAL AND METHODS
    4. CONCLUSION
    5. REFERENCES
    6. ADDITIONAL READING
    7. KEY TERMS AND DEFINITIONS
  10. Chapter 5: Automatic Fruit Disease Classification Using Images
    1. ABSTRACT
    2. INTRODUCTION
    3. LITERATURE REVIEW
    4. AUTOMATIC FRUIT DISEASE CLASSIFICATION
    5. RESULTS AND DISCUSSIONS
    6. CONCLUSION
    7. REFERENCES
    8. ADDITIONAL READING
    9. KEY TERMS AND DEFINITIONS
  11. Chapter 6: Automated Ripeness Assessment System of Tomatoes Using PCA and SVM Techniques
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PRELIMINARIES
    5. THE PROPOSED APPROACH FOR THE AUTOMATED PROCESS OF RIPENESS ASSESSMENT
    6. EXPERIMENTAL RESULTS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  12. Chapter 7: Magnitude and Phase of Discriminative Orthogonal Radial Moments for Face Recognition
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. DISCRIMINATIVE FEATURE ANALYSIS AND FEATURE SELECTION
    5. EXPERIMENTS AND RESULTS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. APPENDIX
  13. Chapter 8: An Efficient System for Blocking Pornography Websites
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORK
    4. SKIN DETECTION TECHNIQUES
    5. FACE DETECTION TECHNIQUES
    6. THE PROPOSED FILTERING SYSTEM
    7. EXPERIMENTAL RESULTS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. REFERENCES
    11. KEY TERMS AND DEFINITIONS
  14. Chapter 9: Online User Interaction Traits in Web-Based Social Biometrics
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. STATE-OF-THE-ART BEHAVIORAL BIOMETRICS
    5. CONCEPT ANALYSIS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  15. Chapter 10: Fingers' Angle Calculation Using Level-Set Method
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND WORK
    4. 3. FINGERS’ ANGLE CALCULATION
    5. 4. EXPERIMENTAL RESULTS
    6. 5. CONCLUSION
    7. ACKNOWLEDGMENT
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  16. Chapter 11: Securing Digital Image with Authentication Code
    1. ABSTRACT
    2. INTRODUCTION
    3. WATERMARKING PROPERTIES AND CLASSIFICATIONS
    4. SOME EXISTING WATERMARKING SCHEMES BASED ON CRYPTOGRAPHIC PRIMITIVES
    5. THE PROPOSED SCHEME
    6. ANALYSIS OF THE PROPOSED SCHEME
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  17. Chapter 12: An Efficient Color Image Encoding Scheme Based on Colorization
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORKS
    4. CHAPTER FUNDAMENTALS
    5. ASSESSMENT METHODS
    6. PROPOSED SYSTEM
    7. EXPERIMENTAL RESULTS AND DISCUSSIONS
    8. FUTURE WORK DIRECTIONS
    9. CONCLUSION
    10. REFERENCES
    11. KEY TERMS AND DEFINITIONS
    12. ENDNOTES
  18. Chapter 13: A Fast New Rotation Insensitive WP-Based Method for Image Indexing and Retrieval
    1. ABSTRACT
    2. INTRODUCTION
    3. THE ALGORITHM
    4. COMPUTER SIMULATIONS AND RESULTS
    5. CONCLUSION
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  19. Chapter 14: Computer Vision-Based Non-Magnetic Object Detection on Moving Conveyors in Steel Industry through Differential Techniques and Performance Evaluation
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED STUDIES
    4. PROBLEM DEFINITION
    5. IMPLEMENTATION
    6. GENERAL MOTION
    7. DIFFERENTIAL METHODS
    8. ALGORITHM
    9. DISCUSSION ON RESULTS
    10. CONCLUSION
    11. REFERENCES
    12. KEY TERMS AND DEFINITIONS
  20. Chapter 15: Detecting Corner Features of Planar Objects
    1. ABSTRACT
    2. INTRODUCTION
    3. BASIC FORMULATION
    4. SUMMARY OF COMMONLY REFERRED CORNER DETECTORS
    5. CHETVERIKOV AND SZABO (CS99) ALGORITHM
    6. EER ALGORITHM
    7. CONCLUDING REMARKS
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  21. Chapter 16: Outline Capture of Planar Objects by Detecting Corner Features
    1. ABSTRACT
    2. INTRODUCTION
    3. COUNTOUR EXTRACTION AND SEGMENTATION
    4. GENERALIZED SPLINE FUNCTIONS
    5. GENETIC ALGORITHM
    6. PROPOSED APPROACH
    7. DEMONSTRATION
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  22. Related References
  23. Compilation of References
  24. About the Contributors