Feature extraction and image processing for computer vision 4th Edition by Mark Nixon, Alberto Aguado 0128149775 9780128149775

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Product details:

ISBN-10 :  0128149775 

ISBN-13 :  9780128149775

Author :  Mark Nixon, Alberto Aguado 

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.

Feature extraction and image processing for computer vision 4th Table of contents:

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

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Tags: Feature extraction, image processing, computer, Mark Nixon, Alberto Aguado