Reader small image

You're reading from  Learning OpenCV 4 Computer Vision with Python 3 - Third Edition

Product typeBook
Published inFeb 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781789531619
Edition3rd Edition
Languages
Tools
Right arrow
Authors (2):
Joseph Howse
Joseph Howse
author image
Joseph Howse

Joseph Howse lives in a Canadian fishing village, where he chats with his cats, crafts his books, and nurtures an orchard of hardy fruit trees. He is President of Nummist Media Corporation, which exists to support his books and to provide mentoring and consulting services, with a specialty in computer vision. On average, in 2015-2022, Joseph has written 1.4 new books or new editions per year for Packt. He also writes fiction, including an upcoming novel about the lives of a group of young people in the last days of the Soviet Union.
Read more about Joseph Howse

Joe Minichino
Joe Minichino
author image
Joe Minichino

Joe Minichino is an R&D labs engineer at Teamwork. He is a passionate programmer who is immensely curious about programming languages and technologies and constantly experimenting with them. Born and raised in Varese, Lombardy, Italy, and coming from a humanistic background in philosophy (at Milan's Università Statale), Joe has lived in Cork, Ireland, since 2004. There, he became a computer science graduate at the Cork Institute of Technology.
Read more about Joe Minichino

View More author details
Right arrow

Understanding types of feature detection and matching

A number of algorithms can be used to detect and describe features, and we will explore several of them in this section. The most commonly used feature detection and descriptor extraction algorithms in OpenCV are as follows:

  • Harris: This algorithm is useful for detecting corners.
  • SIFT: This algorithm is useful for detecting blobs.
  • SURF: This algorithm is useful for detecting blobs.
  • FAST: This algorithm is useful for detecting corners.
  • BRIEF: This algorithm is useful for detecting blobs.
  • ORB: This algorithm stands for Oriented FAST and Rotated BRIEF. It is useful for detecting a combination of corners and blobs.

Matching features can be performed with the following methods:

  • Brute-force matching
  • FLANN-based matching

Spatial verification can then be performed with homography.

We have just introduced a lot of new terminology...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Learning OpenCV 4 Computer Vision with Python 3 - Third Edition
Published in: Feb 2020Publisher: PacktISBN-13: 9781789531619

Authors (2)

author image
Joseph Howse

Joseph Howse lives in a Canadian fishing village, where he chats with his cats, crafts his books, and nurtures an orchard of hardy fruit trees. He is President of Nummist Media Corporation, which exists to support his books and to provide mentoring and consulting services, with a specialty in computer vision. On average, in 2015-2022, Joseph has written 1.4 new books or new editions per year for Packt. He also writes fiction, including an upcoming novel about the lives of a group of young people in the last days of the Soviet Union.
Read more about Joseph Howse

author image
Joe Minichino

Joe Minichino is an R&D labs engineer at Teamwork. He is a passionate programmer who is immensely curious about programming languages and technologies and constantly experimenting with them. Born and raised in Varese, Lombardy, Italy, and coming from a humanistic background in philosophy (at Milan's Università Statale), Joe has lived in Cork, Ireland, since 2004. There, he became a computer science graduate at the Cork Institute of Technology.
Read more about Joe Minichino