
Over 50 recipes to master this library of programming functions for real-time computer vision
Robert Laganière
Yearly subscription | $220.00 | Monthly subscription | $21.99 |
Overview of OpenCV 2 Computer Vision Application Programming Cookbook
- Teaches you how to program computer vision applications in C++ using the different features of the OpenCV library
- Demonstrates the important structures and functions of OpenCV in detail with complete working examples
- Describes fundamental concepts in computer vision and image processing
- Gives you advice and tips to create more effective object-oriented computer vision programs
- Contains examples with source code and shows results obtained on real images with detailed explanations and the required screenshots
[ Detailed Information ]
Language : EnglishPaperback : 304 pages [ 235mm x 191mm ]
Release Date : May 2011
ISBN : 1849513244
ISBN 13 : 978-1-84951-324-1
Author(s) : Robert Laganière
Topics and Technologies : All Books, Cookbooks, Open Source, Web Graphics & Video
[ Book Links ]
[ In Detail ]
In today's digital world, images are everywhere, and with the advent of powerful and affordable computing devices, it has become possible to create sophisticated applications manipulating images and videos. Adding special effects, enhancing image features, performing object recognition, and reconstructing 3D information are tasks that can be programmed easily with the OpenCV library, which is a widely used open source library that offers a rich set of advanced computer vision algorithms.
OpenCV 2 Computer Vision Application Programming Cookbook will introduce you to numerous computer vision algorithms included in the OpenCV library. You will learn how to read, write, create and manipulate images. You will explore different techniques commonly used in image analysis and how they can be effectively implemented in C++. The book provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and be exposed to important concepts in image analysis that will enable you to build your own computer vision applications.
The book helps you to get started with the library, showing you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. The techniques to process an image and its pixels using the data structures offered by the library are explained in detail. You will learn how to build and manipulate an image histogram; how to detect lines and contours. You will be introduced to the concept of mathematical morphology and image filtering. The detection and use of interest points in computer vision is presented with applications for image matching and object recognition. Techniques to achieve camera calibration and 3D reconstruction are presented.
OpenCV 2 Computer Vision Application Programming Cookbook is your guide to the development of computer vision applications. It is a comprehensive reference that exposes you to computer vision concepts illustrated with extensive examples.
A step-by-step guide to computer vision programming using the C++ Interface of the OpenCV 2 library including advanced concepts
What you will learn from this book :
- Create advanced computer vision applications using sound object-oriented programming practices
- Iterate over an image to process each of its pixels
- Enhance an image or interesting parts of an image using histograms
- Use mathematical morphology to process binary images and to segment images into homogenous regions
- Filter images by modifying their frequency content
- Detect the lines, contours , and objects contained in an image
- Apply different interest point operators in order to characterize an image content
- Exploit the image geometry in order to match different views of a pictured scene
- Calibrate the camera from different image observations
- Reconstruct selected image elements in 3D
Approach
This is a cookbook that shows results obtained on real images with detailed explanations and the relevant screenshots. The recipes contain code accompanied with suitable explanations that will facilitate your learning.
Who this book is written for
If you are a novice C++ programmer who wants to learn how to use the OpenCV library to build computer vision applications, then this cookbook is appropriate for you. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can be used as a companion book in university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision. The book provides a good combination of basic to advanced recipes. Basic knowledge of C++ is required.
OpenCV 2 Computer Vision Application Programming Cookbook
Formats:

Includes free access to the book on PacktLib

This book can also be purchased from: | ![]() |
- Teaches you how to program computer vision applications in C++ using the different features of the OpenCV library
- Demonstrates the important structures and functions of OpenCV in detail with complete working examples
- Describes fundamental concepts in computer vision and image processing
- Gives you advice and tips to create more effective object-oriented computer vision programs
- Contains examples with source code and shows results obtained on real images with detailed explanations and the required screenshots
Book Details
Language : EnglishPaperback : 304 pages [ 235mm x 191mm ]
Release Date : May 2011
ISBN : 1849513244
ISBN 13 : 978-1-84951-324-1
Author(s) : Robert Laganière
Topics and Technologies : All Books, Cookbooks, Open Source, Web Graphics & Video
Table of Contents
PrefaceChapter 1: Playing with Images
Chapter 2: Manipulating the Pixels
Chapter 3: Processing Images with Classes
Chapter 4: Counting the Pixels with Histograms
Chapter 5: Transforming Images with Morphological Operations
Chapter 6: Filtering the Images
Chapter 7: Extracting Lines, Contours, and Components
Chapter 8: Detecting and Matching Interest Points
Chapter 9: Estimating Projective Relations in Images
Chapter 10: Processing Video Sequences
Index
- Chapter 1: Playing with Images
- Introduction
- Installing the OpenCV library
- Creating an OpenCV project with MS Visual C++
- Creating an OpenCV project with Qt
- Loading, displaying, and saving images
- Creating a GUI application using Qt
- Chapter 2: Manipulating the 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
- Defining regions of interest
- Chapter 3: Processing Images with Classes
- Introduction
- Using the Strategy pattern in algorithm design
- Using a Controller to communicate with processing modules
- Using the Singleton design pattern
- Using the Model-View-Controller architecture to design an application
- Converting color spaces
- Chapter 4: Counting the Pixels with Histograms
- Introduction
- Computing the image histogram
- Applying look-up tables to modify 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 histogram comparison
- 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 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 and Matching Interest Points
- Introduction
- Detecting Harris corners
- Detecting FAST features
- Detecting the scale-invariant SURF features
- Describing SURF features
- Chapter 9: Estimating Projective Relations in Images
- Introduction
- Calibrating a camera
- Computing the fundamental matrix of an image pair
- Matching images using random sample consensus
- Computing a homography between two images
- Chapter 10: Processing Video Sequences
- Introduction
- Reading video sequences
- Processing the video frames
- Writing video sequences
- Tracking feature points in video
- Extracting the foreground objects in video
Robert Laganière
Sample chapters
You can view our sample chapters and prefaces of this title on PacktLib or download sample chapters in PDF format.
Find your book in our support section to find errata and to download code samples.
- Create advanced computer vision applications using sound object-oriented programming practices
- Iterate over an image to process each of its pixels
- Enhance an image or interesting parts of an image using histograms
- Use mathematical morphology to process binary images and to segment images into homogenous regions
- Filter images by modifying their frequency content
- Detect the lines, contours , and objects contained in an image
- Apply different interest point operators in order to characterize an image content
- Exploit the image geometry in order to match different views of a pictured scene
- Calibrate the camera from different image observations
- Reconstruct selected image elements in 3D

Annual subscription:
$220.00 per annum
Monthly subscription:
$21.99 per month
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In today's digital world, images are everywhere, and with the advent of powerful and affordable computing devices, it has become possible to create sophisticated applications manipulating images and videos. Adding special effects, enhancing image features, performing object recognition, and reconstructing 3D information are tasks that can be programmed easily with the OpenCV library, which is a widely used open source library that offers a rich set of advanced computer vision algorithms.
OpenCV 2 Computer Vision Application Programming Cookbook will introduce you to numerous computer vision algorithms included in the OpenCV library. You will learn how to read, write, create and manipulate images. You will explore different techniques commonly used in image analysis and how they can be effectively implemented in C++. The book provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and be exposed to important concepts in image analysis that will enable you to build your own computer vision applications.
The book helps you to get started with the library, showing you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. The techniques to process an image and its pixels using the data structures offered by the library are explained in detail. You will learn how to build and manipulate an image histogram; how to detect lines and contours. You will be introduced to the concept of mathematical morphology and image filtering. The detection and use of interest points in computer vision is presented with applications for image matching and object recognition. Techniques to achieve camera calibration and 3D reconstruction are presented.
OpenCV 2 Computer Vision Application Programming Cookbook is your guide to the development of computer vision applications. It is a comprehensive reference that exposes you to computer vision concepts illustrated with extensive examples.
A step-by-step guide to computer vision programming using the C++ Interface of the OpenCV 2 library including advanced concepts
This is a cookbook that shows results obtained on real images with detailed explanations and the relevant screenshots. The recipes contain code accompanied with suitable explanations that will facilitate your learning.
If you are a novice C++ programmer who wants to learn how to use the OpenCV library to build computer vision applications, then this cookbook is appropriate for you. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can be used as a companion book in university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision. The book provides a good combination of basic to advanced recipes. Basic knowledge of C++ is required.