Bibliograph

Learning OpenCV, computer vision with the OpenCV library, by Gary Bradski and Adrian Kaehler

Type

Label

Learning OpenCV, computer vision with the OpenCV library, by Gary Bradski and Adrian Kaehler

Language

eng

Bibliography note

Includes bibliographical references and index

Illustrations

illustrations

Index

index present

Literary Form

non fiction

Main title

Learning OpenCV

Medium

electronic resource

Nature of contents

bibliography

Responsibility statement

by Gary Bradski and Adrian Kaehler

Sub title

computer vision with the OpenCV library

Summary

Providing an introduction to computer vision, the technology that enables computers to 'see' and make decisions based on the data, this book explains how developers, students and hobbyists can add vision to their projects using OpenCV, the widely used free open-source computer vision library., "This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised." -William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data. Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time. Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes: A thorough introduction to OpenCV Getting input from cameras Transforming images Segmenting images and shape matching Pattern recognition, including face detection Tracking and motion in 2 and 3 dimensions 3D reconstruction from stereo vision Machine learning algorithms Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started

Classification