In most images, the most useful information is around certain zones that typically correspond to salient points and regions. In most applications, local processing around these salient points is sufficient as long as these points are stable and distinctive. In this chapter, we will cover a basic introduction to the 2D salient points and features offered by OpenCV. It is important to note the difference between detectors and descriptors. Detectors only extract interest points (local features) on an image, while descriptors obtain relevant information about the neighborhood of these points. Descriptors, as their name suggests, describe the image by proper features. They describe an interest point in a way that is invariant to change in lighting and to small perspective deformations. This can be used to match them with other descriptors (typically extracted from other images). For this purpose, matchers are used. This, in turn, can be used...
OpenCV Essentials
OpenCV Essentials
Overview of this book
Table of Contents (15 chapters)
OpenCV Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Getting Started
Something We Look At – Graphical User Interfaces
First Things First – Image Processing
What's in the Image? Segmentation
Focusing on the Interesting 2D Features
Where's Wally? Object Detection
What Is He Doing? Motion
Advanced Topics
Index
Customer Reviews