Learn OpenCV 4 by Building Projects
Build real-world computer vision and image processing applications with OpenCV and C++
2nd Edition
Published on 23. September 2024
310 pages
978-1-78934-762-3 (ISBN)
Description
Explore OpenCV 4 to create visually appealing cross-platform computer vision applications
Key Features
Understand basic OpenCV 4 concepts and algorithms
Grasp advanced OpenCV techniques such as 3D reconstruction, machine learning, and artificial neural networks
Work with Tesseract OCR, an open-source library to recognize text in images
Book DescriptionOpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you're completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects - Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You'll begin with the installation of OpenCV and the basics of image processing. Then, you'll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch. What you will learn
Install OpenCV 4 on your operating system
Create CMake scripts to compile your C++ application
Understand basic image matrix formats and filters
Explore segmentation and feature extraction techniques
Remove backgrounds from static scenes to identify moving objects for surveillance
Employ various techniques to track objects in a live video
Work with new OpenCV functions for text detection and recognition with Tesseract
Get acquainted with important deep learning tools for image classification
Who this book is forIf you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, Learn OpenCV 4 by Building Projects for you. Prior knowledge of C++ will help you understand the concepts covered in this book.
Key Features
Understand basic OpenCV 4 concepts and algorithms
Grasp advanced OpenCV techniques such as 3D reconstruction, machine learning, and artificial neural networks
Work with Tesseract OCR, an open-source library to recognize text in images
Book DescriptionOpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you're completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects - Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects. You'll begin with the installation of OpenCV and the basics of image processing. Then, you'll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module. By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch. What you will learn
Install OpenCV 4 on your operating system
Create CMake scripts to compile your C++ application
Understand basic image matrix formats and filters
Explore segmentation and feature extraction techniques
Remove backgrounds from static scenes to identify moving objects for surveillance
Employ various techniques to track objects in a live video
Work with new OpenCV functions for text detection and recognition with Tesseract
Get acquainted with important deep learning tools for image classification
Who this book is forIf you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, Learn OpenCV 4 by Building Projects for you. Prior knowledge of C++ will help you understand the concepts covered in this book.
More details
Edition
2nd Revised edition
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Revised edition
File size
76,51 MB
ISBN-13
978-1-78934-762-3 (9781789347623)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
David Millan Escriva | Vinicius G. Mendonca | Prateek Joshi
Learn OpenCV 4 by Building Projects
Build real-world computer vision and image processing applications with OpenCV and C++
Book
11/2018
2nd Edition
Packt Publishing
€67.50
Shipment within 3-4 weeks
Persons
Millan Escriva David :
David Millan Escriva was 8 years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations. In 2005, he finished his studies in IT with honors, through the Universitat Politecnica de Valencia, in human-computer interaction supported by computer vision with OpenCV (v0.96). He has worked with Blender, an open source, 3D software project, and on its first commercial movie, Plumiferos, as a computer graphics software developer. David has more than 10 years' experience in IT, with experience in computer vision, computer graphics, pattern recognition, and machine learning, working on different projects, and at different start-ups, and companies. He currently works as a researcher in computer vision.G. Mendonca Vinicius :
Vinicius G. Mendonca is a professor at PUCPR and a mentor at Apple Developer Academy. He has a master's degree in Computer Vision and Image Processing (PUCPR) and a specialization degree in Game Development (Universidade Positivo). He is also one of the authors of the book Learn OpenCV 4 by Building Projects, also by Packt Publishing. He has been in this field since 1996. His former experience includes designing and programming a multithreaded framework for PBX tests at Siemens, coordination of Aurelio Dictionary software (including its apps for Android, IOS, and Windows phones), and coordination of an augmented reality educational activity for Positivo's Mesa Alfabeto, presented at CEBIT. Currently, he works with server-side Node.js at a company called Tenet Tech.Joshi Prateek :
Prateek Joshi is the founder of Plutoshift and a published author of 9 books on Artificial Intelligence. He has been featured on Forbes 30 Under 30, NBC, Bloomberg, CNBC, TechCrunch, and The Business Journals. He has been an invited speaker at conferences such as TEDx, Global Big Data Conference, Machine Learning Developers Conference, and Silicon Valley Deep Learning. Apart from Artificial Intelligence, some of the topics that excite him are number theory, cryptography, and quantum computing. His greater goal is to make Artificial Intelligence accessible to everyone so that it can impact billions of people around the world.
David Millan Escriva was 8 years old when he wrote his first program on an 8086 PC in Basic, which enabled the 2D plotting of basic equations. In 2005, he finished his studies in IT with honors, through the Universitat Politecnica de Valencia, in human-computer interaction supported by computer vision with OpenCV (v0.96). He has worked with Blender, an open source, 3D software project, and on its first commercial movie, Plumiferos, as a computer graphics software developer. David has more than 10 years' experience in IT, with experience in computer vision, computer graphics, pattern recognition, and machine learning, working on different projects, and at different start-ups, and companies. He currently works as a researcher in computer vision.G. Mendonca Vinicius :
Vinicius G. Mendonca is a professor at PUCPR and a mentor at Apple Developer Academy. He has a master's degree in Computer Vision and Image Processing (PUCPR) and a specialization degree in Game Development (Universidade Positivo). He is also one of the authors of the book Learn OpenCV 4 by Building Projects, also by Packt Publishing. He has been in this field since 1996. His former experience includes designing and programming a multithreaded framework for PBX tests at Siemens, coordination of Aurelio Dictionary software (including its apps for Android, IOS, and Windows phones), and coordination of an augmented reality educational activity for Positivo's Mesa Alfabeto, presented at CEBIT. Currently, he works with server-side Node.js at a company called Tenet Tech.Joshi Prateek :
Prateek Joshi is the founder of Plutoshift and a published author of 9 books on Artificial Intelligence. He has been featured on Forbes 30 Under 30, NBC, Bloomberg, CNBC, TechCrunch, and The Business Journals. He has been an invited speaker at conferences such as TEDx, Global Big Data Conference, Machine Learning Developers Conference, and Silicon Valley Deep Learning. Apart from Artificial Intelligence, some of the topics that excite him are number theory, cryptography, and quantum computing. His greater goal is to make Artificial Intelligence accessible to everyone so that it can impact billions of people around the world.
Content
Table of Contents
Getting started with OpenCV
An introduction to the basics of OpenCV
Learning graphical user interfaces
Delving into histrograms and filters
Automated optical inspection, object segmentation and detection
Learning object classification
Detecting face parts and overlaying masks
Video surveillance, background modeling, and morphological operations
Learning object tracking
Developing segmentation algorithms for text recognition
Text recognition with Tesseract
Deep Learning with OpenCV
Getting started with OpenCV
An introduction to the basics of OpenCV
Learning graphical user interfaces
Delving into histrograms and filters
Automated optical inspection, object segmentation and detection
Learning object classification
Detecting face parts and overlaying masks
Video surveillance, background modeling, and morphological operations
Learning object tracking
Developing segmentation algorithms for text recognition
Text recognition with Tesseract
Deep Learning with OpenCV
