Learn OpenCV 4 by Building Projects: Build real-world computer vision and image processing applications with OpenCV and C++, 2nd Edition

by David Millán Escrivá, Vinícius G. Mendonça, Prateek Joshi

Overview

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 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.

Product Details

ISBN-13:	9781789347623
Publisher:	Packt Publishing
Publication date:	11/30/2018
Sold by:	Barnes & Noble
Format:	eBook
Pages:	310
File size:	79 MB
Note:	This product may take a few minutes to download.

About the Author

David Millán Escrivá 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 Politécnica 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. Vinícius G. Mendonça is a computer graphics university professor at Pontifical Catholic University of Paraná (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. In 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. 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.
David Millán Escrivá was eight 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 through the Universitat Politécnica de Valenci with honors in human-computer interaction supported by computer vision with OpenCV (v0.96). He had a final project based on this subject and published it on HCI Spanish congress. He has worked with Blender, an open source, 3D software project, and worked on his first commercial movie, Plumiferos - Aventuras voladoras, as a computer graphics software developer. David now has more than 10 years of experience in IT, with experience in computer vision, computer graphics, and pattern recognition, working with different projects and start-ups, applying his knowledge of computer vision, optical character recognition, and augmented reality. He is the author of the DamilesBlog blog, where he publishes research articles and tutorials about OpenCV, computer vision in general, and optical character recognition algorithms.

Table of Contents

Table of Contents

1. Getting started with OpenCV
2. An introduction to the basics of OpenCV
3. Learning graphical user interfaces
4. Delving into histrograms and filters
5. Automated optical inspection, object segmentation and detection
6. Learning object classification
7. Detecting face parts and overlaying masks
8. Video surveillance, background modeling, and morphological operations
9. Learning object tracking
10. Developing segmentation algorithms for text recognition
11. Text recognition with Tesseract
12. Deep Learning with OpenCV