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OpenCV Computer Vision Application Programming Cookbook Second Edition

Robert Laganière 著

更新時間：2021-04-02 10:06:17

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OpenCV3ComputerVisionApplicationProgrammingCookbookisappropriatefornoviceC++programmerswhowanttolearnhowtousetheOpenCVlibrarytobuildcomputervisionapplications.Itisalsosuitableforprofessionalsoftwaredeveloperswishingtobeintroducedtotheconceptsofcomputervisionprogramming.Itcanalsobeusedasacompanionbookinauniversity-levelcomputervisioncourses.Itconstitutesanexcellentreferenceforgraduatestudentsandresearchersinimageprocessingandcomputervision.

目錄(90章)

倒序

coverpage
OpenCV Computer Vision Application Programming Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files eBooks discount offers and more
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Playing with Images
Introduction
Installing the OpenCV library
Loading displaying and saving images
Exploring the cv::Mat data structure
Defining regions of interest
Chapter 2. Manipulating Pixels
Introduction
Accessing pixel values
Scanning an image with pointers
Scanning an image with iterators
Writing efficient image-scanning loops
Scanning an image with neighbor access
Performing simple image arithmetic
Remapping an image
Chapter 3. Processing Color Images with Classes
Introduction
Using the Strategy pattern in an algorithm design
Using a Controller design pattern to communicate with processing modules
Converting color representations
Representing colors with hue saturation and brightness
Chapter 4. Counting the Pixels with Histograms
Introduction
Computing the image histogram
Applying look-up tables to modify the image appearance
Equalizing the image histogram
Backprojecting a histogram to detect specific image content
Using the mean shift algorithm to find an object
Retrieving similar images using the histogram comparison
Counting pixels with integral images
Chapter 5. Transforming Images with Morphological Operations
Introduction
Eroding and dilating images using morphological filters
Opening and closing images using morphological filters
Detecting edges and corners using morphological filters
Segmenting images using watersheds
Extracting distinctive regions using MSER
Extracting foreground objects with the GrabCut algorithm
Chapter 6. Filtering the Images
Introduction
Filtering images using low-pass filters
Filtering images using a median filter
Applying directional filters to detect edges
Computing the Laplacian of an image
Chapter 7. Extracting Lines Contours and Components
Introduction
Detecting image contours with the Canny operator
Detecting lines in images with the Hough transform
Fitting a line to a set of points
Extracting the components' contours
Computing components' shape descriptors
Chapter 8. Detecting Interest Points
Introduction
Detecting corners in an image
Detecting features quickly
Detecting scale-invariant features
Detecting FAST features at multiple scales
Chapter 9. Describing and Matching Interest Points
Introduction
Matching local templates
Describing local intensity patterns
Describing keypoints with binary features
Chapter 10. Estimating Projective Relations in Images
Introduction
Calibrating a camera
Computing the fundamental matrix of an image pair
Matching images using a random sample consensus
Computing a homography between two images
Chapter 11. Processing Video Sequences
Introduction
Reading video sequences
Processing the video frames
Writing video sequences
Tracking feature points in a video
Extracting the foreground objects in a video
Index 更新時間：2021-04-02 10:06:17

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OpenCV Computer Vision Application Programming Cookbook Second Edition