OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications


OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications
Authors: Alexey Spizhevoy – Aleksandr Rybnikov
ISBN-10: 1788474449
ISBN-13: 9781788474443
Released: 2018-03-23
Print Length 页数: 385 pages
Publisher finelybook 出版社:‏ Packt

Book Description


OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications
Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs
OpenCV 3 is a native cross-platform library for computer vision,machine learning,and image processing. OpenCV’s convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing a number of recipes that you can use to improve your applications.
In this book,you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then,we’ll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis.
Later,you’ll work on reconstructing a 3D scene from images,converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally,you’ll get acquainted with recent approaches in deep learning and neural networks.
By the end of the book,you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains.
What You Will Learn
Get familiar with low-level image processing methods
See the common linear algebra tools needed in computer vision
Work with different camera models and epipolar geometry
Find out how to detect interesting points in images and compare them
Binarize images and mask out regions of interest
Detect objects and track them in videos
contents
1 Setting up OpenCV
2 Handling Files,Cameras,and GUIs
3 Filtering Images
4 Tracking Faces with Haar Cascades
5 Detecting Foreground/Background Regions and Depth

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