OpenCV 4 Computer Vision Application Programming Cookbook电子书

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Contributors

About the authors

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Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Sections

Getting ready

How to do it…

How it works…

There's more…

See also

Get in touch

Reviews

Playing with Images

Installing the OpenCV library

Getting ready

How to do it...

How it works...

There's more...

Using Qt for OpenCV developments

The OpenCV developer site

See also

Loading, displaying, and saving images

Getting ready

How to do it...

How it works...

There's more...

Clicking on images

Drawing on images

Running the example with Qt

See also

Exploring the cv::Mat data structure

How to do it...

How it works...

There's more...

The input and output arrays

See also

Defining regions of interest

Getting ready

How to do it...

How it works...

There's more...

Using image masks

See also

Manipulating the Pixels

Accessing pixel values

Getting ready

How to do it...

How it works...

There's more...

The cv::Mat_ template class

See also

Scanning an image with pointers

Getting ready

How to do it...

How it works...

There's more...

Other color reduction formulas

Having input and output arguments

Efficient scanning of continuous images

Low-level pointer arithmetics

See also

Scanning an image with iterators

Getting ready

How to do it...

How it works...

There's more...

See also

Writing efficient image-scanning loops

How to do it...

How it works...

There's more...

See also

Scanning an image with neighbor access

Getting ready

How to do it...

How it works...

There's more...

See also

Performing simple image arithmetic

Getting ready

How to do it...

How it works...

There's more...

Overloaded image operators

Splitting the image channels

Remapping an image

How to do it...

How it works...

See also

Processing Color Images with Classes

Comparing colors using the strategy design pattern

How to do it...

How it works...

There's more...

Computing the distance between two color vectors

Using OpenCV functions

The functor or function object

The OpenCV base class for algorithms

See also

Segmenting an image with the GrabCut algorithm

How to do it...

How it works...

See also

Converting color representations

Getting ready

How to do it...

How it works...

See also

Representing colors with hue, saturation, and brightness

How to do it...

How it works...

There's more...

Using colors for detection – skin tone detection

Counting the Pixels with Histograms

Computing the image histogram

Getting started

How to do it...

How it works...

There's more...

Computing histograms of color images

See also

Applying lookup tables to modify the image's appearance

How to do it...

How it works...

There's more...

Stretching a histogram to improve the image contrast

Applying a lookup table on color images

Equalizing the image histogram

How to do it...

How it works...

Backprojecting a histogram to detect specific image content

How to do it...

How it works...

There's more...

Backprojecting color histograms

Using the mean shift algorithm to find an object

How to do it...

How it works...

See also

Retrieving similar images using histogram comparison

How to do it...

How it works...

See also

Counting pixels with integral images

How to do it...

How it works...

There's more...

Adaptive thresholding

Visual tracking using histograms

See also

Transforming Images with Morphological Operations

Eroding and dilating images using morphological filters

Getting ready

How to do it...

How it works...

There's more...

See also

Opening and closing images using morphological filters

How to do it...

How it works...

See also

Detecting edges and corners using morphological filters

Getting ready

How to do it...

How it works...

See also

Segmenting images using watersheds

How to do it...

How it works...

There's more...

See also

Extracting distinctive regions using MSER

How to do it...

How it works...

See also

Extracting foreground objects with the GrabCut algorithm

How to do it...

How it works...

See also

Filtering the Images

Filtering images using low-pass filters

How to do it...

How it works...

See also

Downsampling an image

How to do it...

How it works...

There's more...

Interpolating pixel values

See also

Filtering images using a median filter

How to do it...

How it works...

Applying directional filters to detect edges

How to do it...

How it works...

There's more...

Gradient operators

Gaussian derivatives

See also

Computing the Laplacian of an image

How to do it...

How it works...

There's more...

Enhancing the contrast of an image using the Laplacian

Difference of Gaussians

See also

Extracting Lines, Contours, and Components

Detecting image contours with the Canny operator

How to do it...

How it works...

See also

Detecting lines in images with the Hough transform

Getting ready

How to do it...

How it works...

There's more...

Detecting circles

See also

Fitting a line to a set of points

How to do it...

How it works...

There's more...

Extracting the components' contours

How to do it...

How it works...

There's more...

Computing components' shape descriptors

How to do it...

How it works...

There's more...

Quadrilateral detection

Detecting Interest Points

Detecting corners in an image

How to do it...

How it works...

There's more...

Good features to track

The feature detector's common interface

See also

Detecting features quickly

How to do it...

How it works...

There's more...

Adapted feature detection

See also

Detecting scale-invariant features

How to do it...

How it works...

There's more...

The SIFT feature-detection algorithm

See also

Detecting FAST features at multiple scales

How to do it...

How it works...

There's more...

The ORB feature-detection algorithm

See also

Describing and Matching Interest Points

Matching local templates

How to do it...

How it works...

There's more...

Template matching

See also

Describing local intensity patterns

How to do it...

How it works...

There's more...

Cross-checking matches

The ratio test

Distance thresholding

See also

Describing keypoints with binary features

How to do it...

How it works...

There's more...

FREAK

See also

Estimating Projective Relations in Images

Computing the fundamental matrix of an image pair

Getting ready

How to do it...

How it works...

See also

Matching images using a random sample consensus

How to do it...

How it works...

There's more...

Refining the fundamental matrix

Refining the matches

Computing a homography between two images

Getting ready

How to do it...

How it works...

There's more...

Detecting planar targets in an image

How to do it...

See also

Reconstructing 3D Scenes

Digital image formation

Calibrating a camera

Getting ready

How to do it...

How it works...

There's more...

Calibration with known intrinsic parameters

Using a grid of circles for calibration

See also

Recovering the camera pose

How to do it...

How it works...

There's more...

cv::Viz – a 3D visualizer module

See also

Reconstructing a 3D scene from calibrated cameras

How to do it...

How it works...

There's more...

Decomposing a homography

Bundle adjustment

See also

Computing depth from a stereo image

Getting ready

How to do it...

How it works...

See also

Processing Video Sequences

Reading video sequences

How to do it...

How it works...

There's more...

See also

Processing video frames

How to do it...

How it works...

There's more...

Processing a sequence of images

Using a frame processor class

See also

Writing video sequences

How to do it...

How it works...

There's more...

The codec four-character code

See also

Extracting the foreground objects in a video

How to do it...

How it works...

There's more...

The mixture of Gaussian method

See also

Tracking Visual Motion

Tracing feature points in a video

How to do it...

How it works...

See also

Estimating the optical flow

Getting ready

How to do it...

How it works...

See also

Tracking an object in a video

How to do it...

How it works...

See also

Learning from Examples

Recognizing faces using the nearest neighbors of local binary patterns

How to do it...

How it works...

See also

Finding objects and faces with a cascade of Haar features

Getting ready

How to do it...

How it works...

There's more...

Face detection with a Haar cascade

See also

Detecting objects and people using SVMs and histograms of oriented gradients

Getting ready

How to do it...

How it works...

There's more...

HOG visualization

People detection

Deep learning and convolutional neural networks (CNNs)

See also

OpenCV Advanced Features

Face detection using deep learning

How to do it...

How it works...

See also

Object detection with YOLOv3

How to do it...

How it works...

See also

Enabling Halide to improve efficiency

How to do it...

How it works...

See also

OpenCV.js introduction

How to do it...

How it works...

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