Building Computer Vision Projects with OpenCV 4 and C

Implement complex computer vision algorithms and explore deep learning and face detection

By: David Millan Escriva, Prateek Joshi, Vinicius G. Mendonca, Roy Shilkrot

Write A Review

eText | 30 March 2019 | Edition Number 1

At a Glance

Format
ePUB

eText

$64.89

or 4 interest-free payments of $16.22 with

Free with Kobo Plus Read

Start Free Trial *

Subscribe and read all you want.
$13.99 a month after free trial. Cancel Anytime. Learn more.

Instant online reading in your Booktopia eTextbook Library *

Read online on

Desktop

Tablet

Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

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

Key Features

Discover best practices for engineering and maintaining OpenCV projects
Explore important deep learning tools for image classification
Understand basic image matrix formats and filters

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.

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 learn 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 Millan Escriva
Learn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. Mendonça, and Prateek Joshi

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

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, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better understand the concepts in this Learning Path.