Book Image

OpenCV 4 Computer Vision Application Programming Cookbook - Fourth Edition

By : David Millán Escrivá, Robert Laganiere
Book Image

OpenCV 4 Computer Vision Application Programming Cookbook - Fourth Edition

By: David Millán Escrivá, Robert Laganiere

Overview of this book

OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work with recipes to implement a variety of tasks. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by guiding you through setting up OpenCV, and explaining how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of this book, you'll have the skills you need to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects.
Table of Contents (17 chapters)

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 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. The following steps will help us in computing as follows:

  1. For this operator, we will create a simple class that will...