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OpenCV 3 Computer Vision Application Programming Cookbook

OpenCV 3 Computer Vision Application Programming Cookbook

By : Robert Laganiere
3.5 (2)
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OpenCV 3 Computer Vision Application Programming Cookbook

OpenCV 3 Computer Vision Application Programming Cookbook

3.5 (2)
By: Robert Laganiere

Overview of this book

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Cookbook Third Edition provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering. The most recent methods for image matching and object recognition are described, and you’ll discover how to process video from files or cameras, as well as how to detect and track moving objects. Techniques to achieve camera calibration and perform multiple-view analysis will also be explained. Finally, you’ll also get acquainted with recent approaches in machine learning and object classification.
Table of Contents (15 chapters)
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Introduction

Video signals constitute a rich source of visual information. They are made of a sequence of images, called frames, that are taken at regular time intervals (specified as the frame rate, generally expressed in frames per second) and show a scene in motion. With the advent of powerful computers, it is now possible to perform advanced visual analysis on video sequences-sometimes at rates close to, or even faster than, the actual video frame rate. This chapter will show you how to read, process, and store video sequences.

We will see that once the individual frames of a video sequence have been extracted, the different image processing functions presented in this book can be applied to each of them. In addition, we will also look at algorithms that perform a temporal analysis of the video sequence, comparing adjacent frames and accumulating image statistics over time in order to extract foreground objects.

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