Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

By : Robert Laganiere
Book Image

OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

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 (21 chapters)
OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Downsampling images with filters


Images often need to be resized (resampled). The process of reducing the size of an image is often called downsampling, while increasing its size is upsampling. The challenge in performing these operations is to ensure that the visual quality of the image is preserved as much as possible. To accomplish this objective, low-pass filters are often used; this recipe explains why.

How to do it...

You might think that you can reduce the size of an image by simply eliminating some of the columns and rows of the image. Unfortunately, the resulting image will not look very nice. The following figure illustrates this fact by showing you a test image that is reduced by a factor of 4 with respect to its original size by simply keeping 1 of every 4 columns and rows.

Note that to make the defects in this image more apparent, we zoom in on the image by displaying it with pixels that are four times larger:

Clearly, one can see that the image quality has degraded. For example...