Harris Corner Detector

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

Corner를 정의하기 위한 값을 찾는 방법이다.

Harris Corner Detector는 1988년에 발표된 "A COMBINED CORNER AND EDGE DETECTOR" 논문의 저자 중 한 명인 Chris Harris의 이름을 따온 것입니다. 원리는 서로 다른 Frame(이미지)에서 영역(Window)을 설정하고 두 개의 Frame 간의 차이에 대한 제곱합(SSD, Sum of Squared Difference)을 이용하여 현저한 값을 가지는 곳을 Corner로 정의합니다. 여기서, 현저한 값을 추출하기 위해 특정 행렬의 Eigenvalue를 이용합니다.

See also

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

Favorite site

• Wikipedia (en) Harris Corner Detector
• [추천] WORLD of NEO - Harris Corner Detector란 무엇인가 ¹
• (파이썬 OpenCV) 영상의 코너 검출 - Harris, GFTT, FAST - cv2.FastFeatureDetector_create, cv2.goodFeaturesToTrack - Harris, GFTT, FAST OpenCV 예제

References