Build with OpenCV (English Edition)

Develop real-world applications in OpenCV with the latest in computer vision and image processing

About This Book

Get to grips with the basics of computer vision and image processing

Learn OpenCV concepts by building real-world projects

Understand segmentation and feature extraction techniques

Work with Tesseract OCR, a free, open-source library to recognize text in images

Who This Book Is For

This course is for developers who are new to OpenCV and want to develop computer vision applications with OpenCV in C++. A basic knowledge of C++ would be helpful. This course is also useful for people who want to get started with computer vision and understand the underlying concepts. They should be aware of basic mathematical concepts to make the most out of this book.

What You Will Learn

Create the required CMake scripts to compile the C++ application and manage its dependencies

Get to grips with the computer vision workflows and understand the basic image matrix format and filters

Remove backgrounds from a static scene to identify moving objects for video surveillance

Track different objects in a live video using various techniqu

Use the new OpenCV functions for text detection and recognition with Tesseract

In Detail

OpenCV is a cross-platform, free-to-use library that is primarily used for real-time computer vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.

Starting with the installation of OpenCV on your system and understanding the basics of image processing, we will swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly used computer vision techniques to build your own OpenCV projects from scratch. We will develop awesome projects that will focus on the different concepts of computer vision such as image processing, motion detection, and image segmentation. By the end of this course, you will be familiar with the basics of OpenCV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition.

This course will take you through the commonly used Computer Vision techniques to build your own OpenCV projects from scratch.

Style and approach

This course has been designed to teach you OpenCV through the use of projects and learning recipes, and equip you with skills to develop your own cool applications.

This course is a blend of text, videos, code examples, and assessments, all packaged up keeping your journey in mind. The curator of this course has combined some of the best that Packt has to offer in one complete package. It includes content from the following Packt products:

OpenCV 3 by Example [Video] by Prateek Joshi, David Millán Escrivá, Vinícius Godoy

OpenCV by Example by Prateek Joshi, David Millán Escrivá, Vinícius Godoy

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition by Robert Laganiere

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