Feature Extraction and Image Processing for Computer Vision
- 5th Edition - October 3, 2025
- Latest edition
- Authors: Mark Nixon, Alberto S. Aguado
- Language: English
Feature Extraction and Image Processing for Computer Vision, Fifth Edition is an essential guide to the implementation of image processing and computer vision techniques, with t… Read more
Feature Extraction and Image Processing for Computer Vision, Fifth Edition 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, providing a link between theory and implementation. 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.
- Concentrates on feature extraction with working implementation and worked through mathematical derivations and algorithmic methods
- Provides a thorough overview of available feature extraction methods, including essential background theory, shape methods, texture and deep learning
- Includes up-to-date coverage of interest point detection, feature extraction and description, and image representation (including frequency domain and color)
- Includes a good balance between providing a mathematical background and practical implementation
Researchers and graduate students in computer vision, image and video processing
1. Introduction
2. Images, sampling and frequency-domain processing
3. Image processing
4. Distance, Classification and Deep Learning
5. Low-level feature extraction (including Edge Detection)
6. High-level feature extraction: Fixed shape analysis
7. High Level Feature Extraction: Deformable Shape Analysis
8. Object Description
9. Filtering/denoising and region-based analysis
10. Moving Object Detection, Description and Tracking
11. Camera Geometry Fundamentals
12. Colour Images
2. Images, sampling and frequency-domain processing
3. Image processing
4. Distance, Classification and Deep Learning
5. Low-level feature extraction (including Edge Detection)
6. High-level feature extraction: Fixed shape analysis
7. High Level Feature Extraction: Deformable Shape Analysis
8. Object Description
9. Filtering/denoising and region-based analysis
10. Moving Object Detection, Description and Tracking
11. Camera Geometry Fundamentals
12. Colour Images
- Edition: 5
- Latest edition
- Published: October 3, 2025
- Language: English
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Mark Nixon
Mark Nixon is the Professor in Computer Vision at the University of Southampton UK. His research interests are in image processing and computer vision. His team develops new techniques for static and moving shape extraction which have found application in biometrics and in medical image analysis. His team were early workers in automatic face recognition, later came to pioneer gait recognition and more recently joined the pioneers of ear biometrics. With Tieniu Tan and Rama Chellappa, their book Human ID based on Gait is part of the Springer Series on Biometrics and was published in 2005. He has chaired/ program chaired many conferences (BMVC 98, AVBPA 03, IEEE Face and Gesture FG06, ICPR 04, ICB 09, IEEE BTAS 2010) and given many invited talks. Dr. Nixon is a Fellow IET and a Fellow IAPR.
Affiliations and expertise
Professor of Electronics and Computer Science, University of Southampton, UKAA
Alberto S. Aguado
Alberto Aguado is a Lead Programmer at Rare Ltd., Microsoft, UK
Affiliations and expertise
Lead Programmer, Rare Ltd., Microsoft, UKRead Feature Extraction and Image Processing for Computer Vision on ScienceDirect