Browse Library
Sign In Start Free Trial
Close icon Search icon
Account
Browse Library Sign In Start Free Trial

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying OpenCV Computer Vision Application Programming Cookbook Second Edition
  • Table Of Contents Toc
OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
3.7 (3)
Buy this Book
close
close
OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

3.7 (3)
By: Robert Laganiere
Buy this Book

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
close
close
close
Preface
Icon
Preface
Icon
What this book covers
Icon
What you need for this book
Icon
Who this book is for
Icon
Conventions
Icon
Reader feedback
Icon
Customer support
Lock Free Chapter
1
1. Playing with Images
Icon
1. Playing with Images
Icon
Introduction
Icon
Installing the OpenCV library
Icon
Loading, displaying, and saving images
Icon
Exploring the cv::Mat data structure
Icon
Defining regions of interest
2
2. Manipulating Pixels
Icon
2. Manipulating Pixels
Icon
Introduction
Icon
Accessing pixel values
Icon
Scanning an image with pointers
Icon
Scanning an image with iterators
Icon
Writing efficient image-scanning loops
Icon
Scanning an image with neighbor access
Icon
Performing simple image arithmetic
Icon
Remapping an image
3
3. Processing Color Images with Classes
chevron up
Icon
3. Processing Color Images with Classes
Icon
Introduction
Icon
Using the Strategy pattern in an algorithm design
Icon
Using a Controller design pattern to communicate with processing modules
Icon
Converting color representations
Icon
Representing colors with hue, saturation, and brightness
4
4. Counting the Pixels with Histograms
Icon
4. Counting the Pixels with Histograms
Icon
Introduction
Icon
Computing the image histogram
Icon
Applying look-up tables to modify the image appearance
Icon
Equalizing the image histogram
Icon
Backprojecting a histogram to detect specific image content
Icon
Using the mean shift algorithm to find an object
Icon
Retrieving similar images using the histogram comparison
Icon
Counting pixels with integral images
5
5. Transforming Images with Morphological Operations
Icon
5. Transforming Images with Morphological Operations
Icon
Introduction
Icon
Eroding and dilating images using morphological filters
Icon
Opening and closing images using morphological filters
Icon
Detecting edges and corners using morphological filters
Icon
Segmenting images using watersheds
Icon
Extracting distinctive regions using MSER
Icon
Extracting foreground objects with the GrabCut algorithm
6
6. Filtering the Images
Icon
6. Filtering the Images
Icon
Introduction
Icon
Filtering images using low-pass filters
Icon
Filtering images using a median filter
Icon
Applying directional filters to detect edges
Icon
Computing the Laplacian of an image
7
7. Extracting Lines, Contours, and Components
Icon
7. Extracting Lines, Contours, and Components
Icon
Introduction
Icon
Detecting image contours with the Canny operator
Icon
Detecting lines in images with the Hough transform
Icon
Fitting a line to a set of points
Icon
Extracting the components' contours
Icon
Computing components' shape descriptors
8
8. Detecting Interest Points
Icon
8. Detecting Interest Points
Icon
Introduction
Icon
Detecting corners in an image
Icon
Detecting features quickly
Icon
Detecting scale-invariant features
Icon
Detecting FAST features at multiple scales
9
9. Describing and Matching Interest Points
Icon
9. Describing and Matching Interest Points
Icon
Introduction
Icon
Matching local templates
Icon
Describing local intensity patterns
Icon
Describing keypoints with binary features
10
10. Estimating Projective Relations in Images
Icon
10. Estimating Projective Relations in Images
Icon
Introduction
Icon
Calibrating a camera
Icon
Computing the fundamental matrix of an image pair
Icon
Matching images using a random sample consensus
Icon
Computing a homography between two images
11
11. Processing Video Sequences
Icon
11. Processing Video Sequences
Icon
Introduction
Icon
Reading video sequences
Icon
Processing the video frames
Icon
Writing video sequences
Icon
Tracking feature points in a video
Icon
Extracting the foreground objects in a video
12
Index
Icon
Index

Using a Controller design pattern to communicate with processing modules

As you build more complex applications, you will need to create multiple algorithms that can be combined together in order to accomplish some advanced tasks. Consequently, to properly set up the application and have all the classes communicate together will become more and more complex. It then becomes advantageous to centralize the control of the application in a single class. This is the idea behind the Controller design pattern. A Controller is a particular object that plays a central role in an application, and we will explore this in this recipe.

Getting ready

Using your favorite IDE, create a simple dialog-based application with two buttons; one button to select an image, and another button to start the processing, shown as follows:

Getting ready

Here, we use the ColorDetector class of the previous recipe.

How to do it…

The role of the Controller class is to first create the classes required to execute the application. Here...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
OpenCV Computer Vision Application Programming Cookbook Second Edition
End of Section 3
Next Section
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options
font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected
Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful
Order Page Read Now

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon