Book Image

Learning OpenCV 3 Computer Vision with Python

Book Image

Learning OpenCV 3 Computer Vision with Python

Overview of this book

Table of Contents (16 chapters)
Learning OpenCV 3 Computer Vision with Python Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
6
Retrieving Images and Searching Using Image Descriptors
Index

Feature detection algorithms


There are a number of algorithms that can be used to detect and extract features, and we will explore most of them. The most common algorithms used in OpenCV are as follows:

  • Harris: This algorithm is useful to detect corners

  • SIFT: This algorithm is useful to detect blobs

  • SURF: This algorithm is useful to detect blobs

  • FAST: This algorithm is useful to detect corners

  • BRIEF: This algorithm is useful to detect blobs

  • ORB: This algorithm stands for Oriented FAST and Rotated BRIEF

Matching features can be performed with the following methods:

  • Brute-Force matching

  • FLANN-based matching

Spatial verification can then be performed with homography.

Defining features

What is a feature exactly? Why is a particular area of an image classifiable as a feature, while others are not? Broadly speaking, a feature is an area of interest in the image that is unique or easily recognizable. As you can imagine, corners and high-density areas are good features, while patterns that repeat themselves...