Image Pattern Recognition

Image Pattern Recognition

by L Rao, Md. Ur Rahman, P Rohini
Released February 2022
Publisher(s): CRC Press
ISBN: 9781000460971

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Book description

The comprehensive textbook discusses fundamental of data retrieval, image retrieval using extrema patterns in a single volume. It will serve as an ideal study material for senior undergraduate and graduate students in the fields of electrical engineering and electronics and communications engineering.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Contents
  7. Preface
  8. Acknowledgments
  9. Authors
  10. 1 Introduction
    1. 1.1 Data Retrieval
    2. 1.2 Content-Based Image Retrieval System
      1. 1.2.1 Image Databases
      2. 1.2.2 Extraction of Features and the Creation of Feature Database
      3. 1.2.3 Query Image
      4. 1.2.4 Image Matching and Indexing
      5. 1.2.5 Similarity Distance Measures
      6. 1.2.6 Relevance Feedback
      7. 1.2.7 Performance Measures
    3. 1.3 Organization of the Book
  11. 2 Features Used for Image Retrieval Systems
    1. 2.1 Introduction
    2. 2.2 Color Features
    3. 2.3 Texture Features
    4. 2.4 Local Features
    5. 2.5 Shape Features
    6. 2.6 Multiple Features
    7. 2.7 Problem Statement
    8. 2.8 Methodology
  12. 3 Improved Directional Local Extrema Patterns
    1. 3.1 Introduction
    2. 3.2 Local Patterns
      1. 3.2.1 Local Binary Patterns
      2. 3.2.2 Block-Based Local Binary Patterns
      3. 3.2.3 Center-Symmetric Local Binary Patterns
      4. 3.2.4 Local Directional Pattern
    3. 3.3 Directional Local Extrema Patterns
    4. 3.4 Improved Directional Local Extrema Patterns
      1. 3.4.1 Combination of Color and DLEP
      2. 3.4.2 Combination of DLEP and Gabor features
    5. 3.5 Conclusion
    6. Solved Problems
      1. Solution:
      2. Solution:
      3. Solution:
      4. Solution:
      5. Solution:
    7. Histogram
    8. Exercises
  13. 4 Local Quantized Extrema Patterns
    1. 4.1 Introduction
      1. 4.1.1 Local Quantized Patterns
    2. 4.2 Local Quantized Extrema Patterns
      1. 4.2.1 Proposed Image Retrieval System
    3. 4.3 Experimental Results and Discussion
      1. 4.3.1 Corel-1k Database
      2. 4.3.2 Corel-5k Database
      3. 4.3.3 MIT VisTex Database
    4. 4.4 Conclusion
    5. Solved Problems
    6. Exercises
  14. 5 Local Color Oppugnant Quantized Extrema Patterns
    1. 5.1 Introduction
    2. 5.2 Local Color Oppugnant Quantized Extrema Patterns
      1. 5.2.1 Proposed Image Retrieval System
    3. 5.3 Experimental Results and Discussion
      1. 5.3.1 Corel-1k Database
      2. 5.3.2 Corel-5k Database
      3. 5.3.3 Corel-10k Database
      4. 5.3.4 ImageNet-25k Database
    4. 5.4 Conclusion
    5. Solved Problems
    6. Exercises
  15. 6 Local Mesh Quantized Extrema Patterns
    1. 6.1 Introduction
    2. 6.2 Local Mesh Quantized Extrema Patterns
      1. 6.2.1 Proposed Image Retrieval System
    3. 6.3 Experimental Results and Discussion
      1. 6.3.1 MIT VisTex Database
      2. 6.3.2 Corel-1k
    4. 6.4 Conclusion
    5. Solved Problems
    6. Exercises
  16. 7 Local Patterns for Feature Extraction
    1. 7.1 Quantized Neighborhood Local Intensity Extrema Patterns for Image Retrieval
      1. 7.1.1 Introduction
      2. 7.1.2 Major Advantages Over Other Methods
      3. 7.1.3 Framework of the Proposed Retrieval System
      4. 7.1.4 Image Similarity Measurement
      5. 7.1.5 Experimental Results and Discussion
        1. 7.1.5.1 Database: 1
        2. 7.1.5.2 Database: 2
        3. 7.1.5.3 Database: 3
        4. 7.1.5.4 Database: 4
      6. 7.1.6 Conclusion
    2. 7.2 Magnitude Directional Local Extrema Patterns
      1. 7.2.1 Introduction
        1. 7.2.1.1 Contribution
        2. 7.2.1.2 Review of Related Work
      2. 7.2.2 Different Types of Local Patterns
        1. 7.2.2.1 Local Binary Pattern
        2. 7.2.2.2 Local Directional Pattern
        3. 7.2.2.3 Directional Local Extrema Patterns
        4. 7.2.2.4 Magnitude Directional Local Extrema Patterns
      3. 7.2.3 The Proposed CMDLEP System
      4. 7.2.4 Experimental Results
      5. 7.2.5 Conclusion
    3. 7.3 Combination of CDLEP and Gabor Features
      1. 7.3.1 Introduction
        1. 7.3.1.1 Contribution
        2. 7.3.1.2 Related Work
      2. 7.3.2 Gabor Feature
      3. 7.3.3 The Proposed Gabor CDLEP System
      4. 7.3.4 Experimental Results
      5. 7.3.5 Conclusion
    4. 7.4 LEMP: A Robust Image Feature Descriptor for Retrieval Applications
      1. 7.4.1 Introduction
      2. 7.4.2 Relevant Work
        1. 7.4.2.1 Prime Contributions
      3. 7.4.3 Related Local Patterns
        1. 7.4.3.1 Local Binary Patterns
        2. 7.4.3.2 Line Edge Binary Patterns
        3. 7.4.3.3 Line Edge Magnitude Patterns
      4. 7.4.4 The Proposed Framework
        1. 7.4.4.1 Similarity Measurement
        2. 7.4.4.2 Performance Evaluation and Discussions
        3. 7.4.4.3 Corel-1000 Database
        4. 7.4.4.4 Corel 5000 Database (DB2)
      5. 7.4.5 Conclusion
    5. 7.5 Multiple Color Channel Local Extrema Patterns for Image Retrieval
      1. 7.5.1 Introduction
      2. 7.5.2 Relevant Work
        1. 7.5.2.1 Local Quantized Extrema Patterns
      3. 7.5.3 The Proposed Method
      4. 7.5.4 A MCLEP Feature Vector
      5. 7.5.5 Experimental Results and Discussions
        1. 7.5.5.1 Corel-10k
        2. 7.5.5.2 ImageNet-25K
      6. 7.5.6 Conclusion
    6. 7.6 Integration of MDLEP and Gabor Function as a Feature Vector for Image Retrieval System
      1. 7.6.1 Introduction
        1. 7.6.1.1 Related Work
      2. 7.6.2 Local Patterns and Variations
        1. 7.6.2.1 Directional Local Extrema Patterns
        2. 7.6.2.2 Magnitude Directional Local Extrema Patterns (MDLEP)
      3. 7.6.3 Proposed CMDLEP System
      4. 7.6.4 Experimental Results
      5. 7.6.5 Conclusion
    7. 7.7 Content-Based Medical Image Retrieval Using Local Co-Occurrence Patterns
      1. 7.7.1 Introduction
      2. 7.7.2 Local Patterns
        1. 7.7.2.1 Local Binary Patterns
        2. 7.7.2.2 Local Ternary Patterns
        3. 7.7.2.3 Local Derivative Patterns
        4. 7.7.2.4 Local Co-Occurrence Patterns
      3. 7.7.3 Framework of the Proposed System
        1. 7.7.3.1 Similarity Measure
        2. 7.7.3.2 Evaluation Measures
      4. 7.7.4 Experimental Results and Discussions
      5. 7.7.5 Conclusion
    8. 7.8 Color-Based Multi-Directional Local Motif XoR Patterns for Image Retrieval
      1. 7.8.1 Introduction
      2. 7.8.2 Feature Extraction Methods
        1. 7.8.2.1 HSV Color Space and Color Quantization
        2. 7.8.2.2 Directional Binary Code
        3. 7.8.2.3 Directional Local Motif XoR Patterns
      3. 7.8.3 Proposed Feature Descriptors
        1. 7.8.3.1 Analysis
      4. 7.8.4 Experimental Results and Discussions
        1. 7.8.4.1 Experiment #1
        2. 7.8.4.2 Experiment #2
      5. 7.8.5 Conclusion
    9. 7.9 Quantized Local Trio Patterns for Multimedia Image Retrieval System
      1. 7.9.1 Introduction
      2. 7.9.2 Local Extreme Sign Trio Pattern
      3. 7.9.3 Proposed Method
      4. 7.9.4 Experimental Results and Discussions
        1. 7.9.4.1 Corel-10k
      5. 7.9.5 Conclusion
  17. 8 Conclusion and Future Scope
    1. 8.1 Summary
    2. 8.2 Salient Features
      1. 8.2.1 Improved Directional Local Extrema Patterns
      2. 8.2.2 Local Quantized Extrema Patterns
      3. 8.2.3 Local Color Oppugnant Quantized Extrema Patterns
      4. 8.2.4 Local Mesh Quantized Extrema Patterns
    3. 8.3 Future Scope
  18. References
  19. Index

Product information

  • Title: Image Pattern Recognition
  • Author(s): L Rao, Md. Ur Rahman, P Rohini
  • Release date: February 2022
  • Publisher(s): CRC Press
  • ISBN: 9781000460971