Building Computer Vision Projects with OpenCV 4 and C++

Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms

Building Computer Vision Projects with OpenCV 4 and C++

David Millán Escrivá et al.
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Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms
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Book Details

ISBN 139781838644673
Paperback538 pages

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 already have basic knowledge of its concepts, this Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll get an understanding of how to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch.

This Learning Path includes content from the following Packt books:

  • Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá
  • Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi

Table of Contents

Chapter 14: Explore Structure from Motion with the SfM Module
Chapter 16: Number Plate Recognition with Deep Convolutional Networks
Chapter 17: Face Detection and Recognition with the DNN Module

What You Will Learn

  • Stay up-to-date with algorithmic design approaches for complex computer vision tasks
  • Work with OpenCV's most up-to-date API through various projects
  • Understand 3D scene reconstruction and Structure from Motion (SfM)
  • Study camera calibration and overlay augmented reality (AR) using the ArUco module
  • Create CMake scripts to compile your C++ application
  • Explore segmentation and feature extraction techniques
  • Remove backgrounds from static scenes to identify moving objects for surveillance
  • Work with new OpenCV functions to detect and recognize text with Tesseract

Authors

Table of Contents

Chapter 14: Explore Structure from Motion with the SfM Module
Chapter 16: Number Plate Recognition with Deep Convolutional Networks
Chapter 17: Face Detection and Recognition with the DNN Module

Book Details

ISBN 139781838644673
Paperback538 pages
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