Feature Extraction and Image Processing for Computer Vision, 4th Edition

Feature Extraction and Image Processing for Computer Vision, 4th Edition

by Mark Nixon, Alberto Aguado
Released November 2019
Publisher(s): Academic Press
ISBN: 9780128149775

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Book description

Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained.

This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.

  • The only text to concentrate on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods
  • A thorough overview of available feature extraction methods including essential background theory, shape methods, texture and deep learning
  • Up to date coverage of interest point detection, feature extraction and description and image representation (including frequency domain and colour)
  • Good balance between providing a mathematical background and practical implementation
  • Detailed and explanatory of algorithms in MATLAB and Python

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Preface
  7. 1. Introduction
    1. 1.1. Overview
    2. 1.2. Human and computer vision
    3. 1.3. The human vision system
    4. 1.4. Computer vision systems
    5. 1.5. Processing images
    6. 1.6. Associated literature
    7. 1.7. Conclusions
  8. 2. Images, sampling and frequency domain processing
    1. 2.1. Overview
    2. 2.2. Image formation
    3. 2.3. The Fourier Transform
    4. 2.4. The sampling criterion
    5. 2.5. The discrete Fourier Transform
    6. 2.6. Properties of the Fourier Transform
    7. 2.7. Transforms other than Fourier
    8. 2.8. Applications using frequency domain properties
    9. 2.9. Further reading
  9. 3. Image processing
    1. 3.1. Overview
    2. 3.2. Histograms
    3. 3.3. Point operators
    4. 3.4. Group operations
    5. 3.5. Other image processing operators
    6. 3.6. Mathematical morphology
    7. 3.7. Further reading
  10. 4. Low-level feature extraction (including edge detection)
    1. 4.1. Overview
    2. 4.2. Edge detection
    3. 4.3. Phase congruency
    4. 4.4. Localised feature extraction
    5. 4.5. Describing image motion
    6. 4.6. Further reading
  11. 5. High-level feature extraction: fixed shape matching
    1. 5.1. Overview
    2. 5.2. Thresholding and subtraction
    3. 5.3. Template matching
    4. 5.4. Feature extraction by low-level features
    5. 5.5. Hough transform
    6. 5.6. Further reading
  12. 6. High-level feature extraction: deformable shape analysis
    1. 6.1. Overview
    2. 6.2. Deformable shape analysis
    3. 6.3. Active contours (snakes)
    4. 6.4. Shape Skeletonisation
    5. 6.5. Flexible shape models – active shape and active appearance
    6. 6.6. Further reading
  13. 7. Object description
    1. 7.1. Overview and invariance requirements
    2. 7.2. Boundary descriptions
    3. 7.3. Region descriptors
    4. 7.4. Further reading
  14. 8. Region-based analysis
    1. 8.1. Overview
    2. 8.2. Region-based analysis
    3. 8.3. Texture description and analysis
    4. 8.4. Further reading
  15. 9. Moving object detection and description
    1. 9.1. Overview
    2. 9.2. Moving object detection
    3. 9.3. Tracking moving features
    4. 9.4. Moving feature extraction and description
    5. 9.5. Further reading
  16. 10. Camera geometry fundamentals
    1. 10.1. Overview
    2. 10.2. Projective space
    3. 10.3. The perspective camera
    4. 10.4. Affine camera
    5. 10.5. Weak perspective model
    6. 10.6. Discussion
    7. 10.7. Further reading
  17. 11. Colour images
    1. 11.1. Overview
    2. 11.2. Colour image theory
    3. 11.3. Perception-based colour models: CIE RGB and CIE XYZ
    4. 11.4. Additive and subtractive colour models
    5. 11.5. Luminance and chrominance colour models
    6. 11.6. Additive perceptual colour models
    7. 11.7. More colour models
  18. 12. Distance, classification and learning
    1. 12.1. Overview
    2. 12.2. Basis of classification and learning
    3. 12.3. Distance and classification
    4. 12.4. Neural networks and Support Vector Machines
    5. 12.5. Deep learning
    6. 12.6. Further reading
  19. Index

Product information

  • Title: Feature Extraction and Image Processing for Computer Vision, 4th Edition
  • Author(s): Mark Nixon, Alberto Aguado
  • Release date: November 2019
  • Publisher(s): Academic Press
  • ISBN: 9780128149775