Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

By : Robert Laganiere
Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

By: Robert Laganiere

Overview of this book

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Cookbook Third Edition 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 exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering. The most recent methods for image matching and object recognition are described, and you’ll discover how to process video from files or cameras, as well as how to detect and track moving objects. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. Finally, you’ll also get acquainted with recent approaches in machine learning and object classification.
Table of Contents (21 chapters)
OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Computing components' shape descriptors


A connected component often corresponds to the image of an object in a pictured scene. To identify this object, or to compare it with other image elements, it can be useful to perform some measurements on the component in order to extract some of its characteristics. In this recipe, we will look at some of the shape descriptors available in OpenCV that can be used to describe the shape of a connected component.

How to do it...

Many OpenCV functions are available when it comes to shape description. We will apply some of them on the components that we have extracted in the preceding recipe. In particular, we will use our vector of four contours corresponding to the four buffaloes we previously identified. In the following code snippets, we compute a shape descriptor on the contours (contours[0] to contours[3]) and draw the result (with a thickness of 2) over the image of the contours (with a thickness of 1). This image is shown at the end of this section...