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 the Laplacian of an image


The Laplacian is another high-pass linear filter that is based on the computation of the image derivatives. As it will be explained, it computes second-order derivatives to measure the curvature of the image function.

How to do it...

The OpenCV function, cv::Laplacian, computes the Laplacian of an image. It is very similar to the cv::Sobel function. In fact, it uses the same basic function, cv::getDerivKernels, in order to obtain its kernel matrix. The only difference is that there are no derivative order parameters since these ones are, by definition, second order derivatives.

For this operator, we will create a simple class that will encapsulate some useful operations related to the Laplacian. The basic attributes and methods are as follows:

    class LaplacianZC { 
 
      private: 
      // laplacian 
      cv::Mat laplace; 
      // Aperture size of the laplacian kernel 
      int aperture; 
 
      public: 
...