Learn OpenCV 4 By Building Projects - Second Edition

More Information
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
About

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.

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
Page Count 310
Course Length 9 hours 18 minutes
ISBN 9781789341225
Date Of Publication 30 Nov 2018

Authors

David Millán Escrivá

David Millán Escrivá 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 Politécnica 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.

Prateek Joshi

Prateek Joshi is an artificial intelligence researcher, an author of several 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 venturefunded 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.

Vinícius G. Mendonça

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.