What you need for this book
by Joe Minichino
Learning OpenCV 3 Computer Vision with Python - Second Edition
- Learning OpenCV 3 Computer Vision with Python Second Edition
- Table of Contents
- Learning OpenCV 3 Computer Vision with Python Second Edition
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Setting Up OpenCV
- 2. Handling Files, Cameras, and GUIs
- 3. Processing Images with OpenCV 3
- Converting between different color spaces
- The Fourier Transform
- Creating modules
- Edge detection
- Custom kernels – getting convoluted
- Modifying the application
- Edge detection with Canny
- Contour detection
- Contours – bounding box, minimum area rectangle, and minimum enclosing circle
- Contours – convex contours and the Douglas-Peucker algorithm
- Line and circle detection
- Detecting shapes
- Summary
- 4. Depth Estimation and Segmentation
- 5. Detecting and Recognizing Faces
- 6. Retrieving Images and Searching Using Image Descriptors
- Feature detection algorithms
- Defining features
- Feature extraction and description using DoG and SIFT
- Feature extraction and detection using Fast Hessian and SURF
- ORB feature detection and feature matching
- Feature matching with ORB
- Using K-Nearest Neighbors matching
- FLANN-based matching
- FLANN matching with homography
- A sample application – tattoo forensics
- Summary
- Feature detection algorithms
- 7. Detecting and Recognizing Objects
- 8. Tracking Objects
- 9. Neural Networks with OpenCV – an Introduction
- Index
-
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