Kaehler Bradski Learning OpenCV 3 2017
pdf | 42.56 MB | English | Isbn: B01MRXIYAN | Author: Adrian Kaehler and Gary Bradski | Year: 2016
Description:
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
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.
Category:Computer Hardware DSPs, Pattern Recognition, C Programming
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