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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 you're completely new to computer vision, or have…mehr

Produktbeschreibung
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 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 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. 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
Autorenporträt
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.