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
Researchers and graduate students in computer vision, image and video processing
- Techniques in visual descriptor extraction and representation
2. Overview of visual search and recognition engines
3. Feature quantization and indexing
4. Building recognition models
5. On compact feature learning
6. On deep model compression
8. Trends and Future Research Challenges
- No. of pages:
- © Academic Press 2020
- 1st September 2019
- Academic Press
- Paperback ISBN:
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.
Professor of Electronics and Computer Science, University of Southampton, UK
Alberto Aguado is a principal algorithm researcher and developer at Foundry London were he works developing Image Processing, Computer Vision and rendering technologies for video production. Previously, he was head of research on animation technologies at Natural Motion. He developed image processing technologies for sport tracking at Sportradar. He worked as developer for Electronic Arts and for Black Rock Disney Game Studios. He gained academic experience as a Lecturer in the Centre for Vision, Speech and Signal Processing in the University of Surrey. He pursued a postdoctoral fellowship in Computer Vision at INRIA Rhône-Alpes (Marie Curie fellowship) and he received his PhD in Computer Vision /Image Processing from the University of Southampton.
Principal Programmer, Sportradar, Brighton, UK