Description
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
Table of Contents
1. Introduction2. Images, sampling and frequency-domain processing3. Image processing4. Distance, Classification and Deep Learning5. Low-level feature extraction (including Edge Detection)6. High-level feature extraction: Fixed shape analysis7. High Level Feature Extraction: Deformable Shape Analysis8. Object Description9. Filtering/denoising and region-based analysis10. Moving Object Detection, Description and Tracking11. Camera Geometry Fundamentals12. Colour Images
