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Prateek Joshi - Learn OpenCV 4 by Building Projects

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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 Description

OpenCV 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 youre 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.

Youll begin with the installation of OpenCV and the basics of image processing. Then, youll cover user interfaces and get deeper into image processing. As you progress through the book, youll 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, youll 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, youll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and youll 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 for

If 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.

Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

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Learn OpenCV 4 byBuilding ProjectsSecond Edition Build real-world computer - photo 1
Learn OpenCV 4 byBuilding ProjectsSecond Edition
Build real-world computer vision and image processing applications with OpenCV and C++
David Milln EscrivVincius G. MendonaPrateek Joshi

BIRMINGHAM - MUMBAI Learn OpenCV 4 by Building ProjectsSecond Edition - photo 2

BIRMINGHAM - MUMBAI
Learn OpenCV 4 by Building ProjectsSecond Edition

Copyright 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this ...

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Contributors
About the authors

David Milln Escriv was eight years old when he wrote his first program on an 8086 PC using the BASIC language. He completed his studies in IT from the Universitat Politcnica de Valencia with honors in human-computer interaction supported by computer vision with OpenCV (v0.96). He has a master's degree in artificial intelligence, computer graphics, and pattern recognition, focusing on pattern recognition and computer vision. He also has more than nine years' experience in computer vision, computer graphics, and pattern recognition. He is the author of the Damiles Blog, where he publishes articles and tutorials on OpenCV, computer vision in general, and optical character recognition algorithms.

I would like thank to my wife, Izaskun, my daughter, Eider, and my son, Pau, for their unlimited patience and support at all times. They have changed my life and made it awesome every day. I love you all.
I would like to thank the OpenCV team and community that gives us this wonderful library. I would also like to thank my co-authors and Packt Publishing for supporting me and helping me to complete this book.

Vincius G. Mendona is a computer graphics university professor at Pontifical Catholic University of Paran (PUCPR). He started programming with C++ back in 1998, and ventured into the field of computer gaming and computer graphics back in 2006. He is currently a mentor at the Apple Developer Academy in Brazil, working with, and teaching, metal, machine learning and computer vision for mobile devices. He has served as a reviewer on other Pack books, including OpenNI Cookbook, and Mastering OpenCV and Computer Vision with OpenCV 3 and Qt5. I n his research, he has used Kinect, OpenNI, and OpenCV to recognize Brazilian sign language gestures. His areas of interest include mobile, OpenGL, image processing, computer vision, and project management.

I would like to thank my wife, Thais A. L. Mendona, for the support she gave me while writing this book. I also dedicate this work to my four girls, Laura, Helena, Alice, and Mariana, and to my stepson, Bruno.
My life and work would have no meaning without this great family.
I would also like to thank Fabio Binder my teacher, boss, and mentor who introduced me to computer graphics and gaming fields, and who has helped me greatly throughout my career.

Prateek Joshi is an artificial intelligence researcher, an author of eight published books, and a TEDx speaker. He has been featured in Forbes 30 Under 30, CNBC, TechCrunch, Silicon Valley Business Journal, and many more publications. He is the founder of Pluto AI, a venture-funded Silicon Valley start-up building an intelligence platform for water facilities. He graduated from the University of Southern California with a Master's degree specializing in Artificial Intelligence. He has previously worked at NVIDIA and Microsoft Research.

About the reviewers

Marc Amberg is an experienced machine learning and computer vision engineer with a proven history of working in the IT and service industries. He is skilled in Python, C/C++, OpenGL, 3D Reconstruction, and Java. He is a strong engineering professional with a master's degree focused on computer science (Image, Vision, and Interactions) from Universit des Sciences et Technologies de Lille (Lille I).

Vincent Kok currently works as a software platform application engineer with Intel in the transportation industry sector. He graduated from the University Sains Malaysia (USM) with a degree in electronic engineering. Currently, he is pursuing his master's degree in embedded system engineering at USM. Vincent actively involves ...

What this book covers

, Getting Started with OpenCV, covers installation steps on various operating systems and provides an introduction to the human visual system, as well as various topics in computer vision.

, Introduction to OpenCV Basics, discusses how to read/write images and videos in OpenCV, and also explains how to build a project using CMake.

, Learning Graphical User Interface and Basic Filtering, covers how to build a graphical user interface and mouse event detector to build interactive applications.

, Delving into Histograms and Filters, explores histograms and filters and also shows how we can cartoonize an image.

, Automated Optical Inspection, Object Segmentation, and Detection, describes various image pre-processing techniques, such as noise removal, thresholding, and contour analysis.

, Learning Object Classification, deals with object recognition and machine learning, and how to use support vector machines to build an object classification system.

, Detecting Face Parts and Overlaying Masks

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