Harris Corner Detector

lastmod 2024-03-04created 2019-12-069 edits

Harris Corner Detector is a corner detection operator that is commonly used in computer vision algorithms to extract corners and infer features of an image. It was first introduced by Chris Harris and Mike Stephens in 1988 upon the improvement of Moravec's corner detector. Compared to the previous one, Harris' corner detector takes the differential of the corner score into account with reference to direction directly, instead of using shifting patches for every 45 degree angles, and has been proved to be more accurate in distinguishing between edges and corners. Since then, it has been improved and adopted in many algorithms to preprocess images for subsequent applications.

About

A method for finding values that define a corner.

The Harris Corner Detector is named after Chris Harris, one of the authors of the paper "A COMBINED CORNER AND EDGE DETECTOR" published in 1988. The principle is: set a region (Window) in different Frames (images), and define places with salient values as Corners using the Sum of Squared Differences (SSD) between the two Frames. Here, the Eigenvalues of a particular matrix are used to extract the salient values.

See also

• Feature detection
• Oriented FAST and rotated BRIEF (ORB)

Favorite site

• Wikipedia (en) Harris Corner Detector
• [Recommended] WORLD of NEO - What is the Harris Corner Detector ¹
• (Python OpenCV) Corner detection in images - Harris, GFTT, FAST - cv2.FastFeatureDetector_create, cv2.goodFeaturesToTrack - Harris, GFTT, FAST OpenCV examples

References