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)

Eroding and dilating images using morphological filters

Erosion and dilation are the most fundamental morphological operators. Therefore, we will present these in the first recipe of this chapter. The fundamental component in mathematical morphology is the structuring element. A structuring element can be simply defined as a configuration of pixels (the square shape in the following diagram) on which an origin is defined (also called an anchor point). Applying a morphological filter consists of probing each pixel of the image using this structuring element. When the origin of the structuring element is aligned with a given pixel, its intersection with the image defines a set of pixels on which a particular morphological operation is applied (the nine shaded pixels in the following figure). In principle, the structuring element can be of any shape, but most often, a simple shape...