Learning OpenCV 3 Computer vision in C with the OpenCV library 1st Edition by Kaehler, Bradski 9781491938003 1491938005

Instant download Learning OpenCV 3 Computer vision in C with the OpenCV library Adrian Kaehler & Gary Bradski pdf, docx, kindle format all chapters after payment. ISBN(s): 9781491938003, 1491938005

Product details:

• ISBN 10: 1491938005
• ISBN 13: 9781491938003
• Author: Kaehler, Bradski

Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You’ll learn what it takes to build applications that enable computers to “see” and make decisions based on that data. With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you’ve learned. This volume covers the entire library, in its modern C implementation, including machine learning tools for computer vision. Learn OpenCV data types, array types, and array operations Capture and store still and video images with HighGUI Transform images to stretch, shrink, warp, remap, and repair Explore pattern recognition, including face detection Track objects and motion through the visual field Reconstruct 3D images from stereo vision Discover basic and advanced machine learning techniques in OpenCV

Table contents:

1. Overview

2. Introduction to OpenCV

3. Getting to Know OpenCV Data Types

4. Images and Large Array Types

5. Array Operations

6. Drawing and Annotating

7. Functors in OpenCV

8. Image, Video, and Data Files

9. Cross-Platform and Native Windows

10. Filters and Convolution

11. General Image Transforms

12. Image Analysis

13. Histograms and Templates

14. Contours

15. Background Subtraction

16. Keypoints and Descriptors

17. Tracking

18. Camera Models and Calibration

19. Projection and Three-Dimensional Vision

20. The Basics of Machine Learning in OpenCV

21. StatModel: The Standard Model for Learning in OpenCV

22. Object Detection

23. Future of OpenCV

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