Learn OpenCV 4 by building projects : build real-world computer vision and image processing applications with OpenCV and C++ / David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi

Previous edition published: 2016

Includes bibliographical references and index

Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Getting Started with OpenCV; Understanding the human visual system; How do humans understand image content?; Why is it difficult for machines to understand image content?; What can you do with OpenCV?; Inbuilt data structures and input/output; Image processing operations; GUI; Video analysis; 3D reconstruction; Feature extraction; Object detection; Machine learning; Computational photography; Shape analysis; Optical flow algorithms; Face and object recognition; Surface matching

Text detection and recognitionDeep learning; Installing OpenCV; Windows; Mac OS X; Linux; Summary; Chapter 2: An Introduction to the Basics of OpenCV; Technical requirements; Basic CMake configuration file; Creating a library; Managing dependencies; Making the script more complex; Images and matrices; Reading/writing images; Reading videos and cameras; Other basic object types; Vec object type; Scalar object type; Point object type; Size object type; Rect object type; RotatedRect object type; Basic matrix operations; Basic data persistence and storage; Writing to FileStorage; Summary

Chapter 3: Learning Graphical User InterfacesTechnical requirements; Introducing the OpenCV user interface; Basic graphical user interface with OpenCV; Adding slider and mouse events to our interfaces; Graphic user interface with Qt; Adding buttons to the user interface; OpenGL support; Summary; Chapter 4: Delving into Histogram and Filters; Technical requirements; Generating a CMake script file; Creating the graphical user interface; Drawing a histogram; Image color equalization; Lomography effect; Cartoonize effect; Summary

Chapter 5: Automated Optical Inspection, Object Segmentation, and DetectionTechnical requirements; Isolating objects in a scene; Creating an application for AOI; Preprocessing the input image; Noise removal; Removing the background using the light pattern for segmentation; Thresholding; Segmenting our input image; The connected components algorithm; The findContours algorithm; Summary; Chapter 6: Learning Object Classification; Technical requirements; Introducing machine learning concepts; OpenCV machine learning algorithms; Computer vision and the machine learning workflow

Automatic object inspection classification exampleFeature extraction; Training an SVM model; Input image prediction; Summary; Chapter 7: Detecting Face Parts and Overlaying Masks; Technical requirements; Understanding Haar cascades; What are integral images?; Overlaying a face mask in a live video; What happened in the code?; Get your sunglasses on; Looking inside the code; Tracking the nose, mouth, and ears; Summary; Chapter 8: Video Surveillance, Background Modeling, and Morphological Operations; Technical requirements; Understanding background subtraction; Naive background subtraction

OpenCV is mainly used in Computer Vision and image processing and is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation. This book will be your guide to understanding the basic OpenCV concepts and algorithms