Free E Book OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications

Free E Book OpenCV 4 Computer Vision Application Programming Cookbook Build complex computer vision applications

OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision applications with OpenCV and C++, 4th Edition

OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision applications with OpenCV and C++, 4th Edition

OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision applications with OpenCV and C++, 4th Edition

Author(s): David Millán Escrivá; Robert Laganiere
Publisher: Packt Publishing Ltd, Year: 2019
ISBN: 9781789345285,1789345286


Discover interesting recipes to help you understand the concepts of object detection, image processing and face detection Key Features Explore the latest features and APIs in OpenCV 4 and create computer vision algorithms Develop effective, robust and secure visibility of your applications. Vision algorithms with machine learning capabilities OpenCV book description is an image and video processing library used for all types of image and video analysis.

Throughout the book, you will work through recipes that perform a variety of tasks, such as facial recognition and discovery. 

With 70 stand-alone tutorials, this book looks at common pain points and best practices for computer vision developers (CV). Each recipe covers a specific problem and provides a proven solution and best practices with insight into how it works, so you can copy code and configuration files and modify them to suit your needs. 

This book begins with setting up OpenCV, and explains how to handle pixels. You will understand how you can manipulate images by categories and calculate pixels using graphs. You will also learn to discover, describe and match points of interest. As you progress through the seasons, you'll be able to master projective relationships in images, reconstruct 3D scenes, tackle video sequences, and track visual movement. 

In the final chapters, you will cover deep learning concepts such as face detection and objects. At the end of the book, you will be able to confidently implement a set of computer vision algorithms to meet the technical requirements of complex CV projects What you will learn Install and create a program using OpenCV library images to homogeneous areas and extract meaningful objects Apply image filters to improve image content Exploiting image engineering to migrate methods Different view of the camera calibration scene viewer from different photo notes Discovering people and things in photos using machine learning techniques Rebuilding a 3D scene from photos Explore face detection with deep learning Who is this book if you are a developer or professional who already uses OpenCV or wants to use it to create A computer vision program, this book is for you.

 You will also find this book useful if you are a C ++ programmer looking to expand your computer vision skill set by learning OpenCV.


Augmented reality, driving assistance, video surveillance; More and more applications Now using computer vision and image analysis techniques, we are still in Childhood in developing new computerized systems capable of understanding The world through a sense of vision. And with a strong and affordable appearance Computers and optical sensors, it has never been easier to create a complex Photography applications.

There are many software tools and libraries that handle pictures and videos, But for everyone who wants to develop smart vision-based applications, the OpenCV library It is the tool to use. OpenCV is an open source library with over 500 optimizers Algorithms for image and video analysis. Since its introduction in 1999, it has been largely Approved as an essential development tool by the community of researchers and developers In seeing the computer.

Intel's OpenCV was developed by a team led by Gary Bradski as an initiative Developing research in the field of vision and promoting the development of rich applications based on vision and rich in central processing. After a series of beta releases, version 1.0 was launched in 2006. a The second major release happened in 2009 with the launch of OpenCV 2, which was suggested Important changes, especially the new C ++ interface, that we use in this book. In 2012, OpenCV reconfigured itself as a nonprofit ( dependent on it
Crowdfunding for its future development.

OpenCV 3 was introduced in 2013; The changes were mainly made to improve ease of use
the library. Its structure has been modified to remove unnecessary dependencies, large
Units were divided into smaller units, and the API was improved. 

This book is The fourth version of the OpenCV Computer Vision Application Application Programming Cookbook, the first One covering OpenCV 4.

All programming recipes were for previous editions Review and update. We have also added new content and new chapters to introduce Readers with better coverage of the basic functions of the library.

This book covers several library features and explains how to use them to accomplish them
Specific tasks. 

Our goal is not to provide detailed coverage of every option you offer OpenCV functionality and classes, but rather to give you the elements you need to build Your apps from A to Z. We also explore basic concepts in the image The analysis describes some important algorithms in computer vision.

For whom is this book

This cookbook is suitable for beginners programmers who want to learn how to use it
OpenCV library for building computer vision applications. It is also suitable for Professional software developers who want to learn about computer concepts Vision programming. 

It can be used as a companion book for computer at the university level Vision cycles. It is an excellent reference for postgraduate students and researchers Image processing and computer vision.

What this book covers

Chapter 1, Playing with Pictures, introduces the OpenCV library and shows you how to build
Simple applications that can read and display images. It also offers basic OpenCV data structures.

Chapter 2, pixel processing, explains how to read an image. Different prescribes Ways to scan the image in order to perform an operation on each pixel.

Chapter 3, Color Image Processing with Chapters, consists of recipes that offer different and targeted design styles that can help you build better computer vision applications. 
it's a The concept of colors is also discussed in the pictures.

Chapter 4, Calculating pixels using graphs, shows you how to calculate an image
Charts and how they can be used to edit an image. 
Different applications depend on Diagrams that achieve image segmentation and object and image detection are presented recovery.

Chapter 5, Transforming images by morphological processes, explores a concept Mathematical morphology. It provides various factors and how they can be used Expose edges, corners, and clips in pictures.

Chapter 6 teaches you image filtering principles of frequency and image analysis Filter. Demonstrates how low and high scroll filters can be applied to images, and It introduces the concept of derivative factors.

Chapter 7, Extraction of Lines, Lines and Components, focuses on revealing geometric figures
Image features. It explains how to extract connected fonts, fonts, and components in a file

Chapter 8, Point of Interest Detection, describes many feature detectors in pictures.

Chapter 9, describing and matching interest points, explains how interest descriptors are
Points can be calculated and used to match points between images.

Chapter 10, Estimating Projective Relationships in Pictures, explores projective relationships that are It is between two pictures in the same scene. It also describes how to discover specific targets in picture.

Chapter 11, Rebuilding 3D Scenes, allows you to reconstruct 3D scene elements From multiple photos and restore the camera position. Also includes a description of Camera calibration process.

Chapter 12, Video Sequencing Handling, provides a framework for reading and writing a video
Sequencing and manipulating their frames. It also shows you how to extract Front objects move in front of the camera.

Chapter 13, Optical Motion Tracking, addresses the problem of optical tracking. Apparently
It shows you how to count the movement shown in the videos, and explains how to track moving objects In a photo sequence.

Chapter 14, Learning from Examples, introduces basic concepts in machine learning. it's a
Demonstrates how object classifiers can be built from image samples.

Chapter 15 covers advanced OpenCV features, the most advanced and newest features

This chapter introduces the reader to modern deep learning models in Artificial intelligence and machine learning. Deep learning is applied to the detection of things,
Independent cars and face recognition. 

This chapter will introduce you to OpenCV.js, a New connectivity conveys web technology directly from OpenCV.

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