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Harris Corner Detection×Blobdeteksjon×
FagfeltDatasynDatasyn
FamilieMachine learningMachine learning
Opprinnelsesår19881998
OpphavspersonChris Harris and Mike StephensTony Lindeberg
TypeInterest point detectorMulti-scale feature detection
Opprinnelig kildeHarris, C., & Stephens, M. (1988). A combined corner and edge detector. Alvey Vision Conference, 147–152. link ↗Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗
AliasHarris Corner Detector, Harris-Stephens Detector, Plessey OperatorConnected component analysis, Region-based detection
Relaterte55
SammendragThe Harris corner detector, introduced by Chris Harris and Mike Stephens in 1988, is a foundational method for identifying corners and interest points in digital images. Harris corners are points where two edges meet at a significant angle, making them stable and repeatable features for image analysis, matching, and 3D reconstruction.Blob detection is a technique for identifying regions of interest (blobs)—connected, homogeneous areas that differ from their surroundings—at multiple scales. Introduced by Lindeberg in the context of scale-space theory, blob detection automatically finds and characterizes circular or elliptical objects without requiring a priori knowledge of their size.
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ScholarGateSammenlign metoder: Harris Corner Detection · Blob Detection. Hentet 2026-06-18 fra https://scholargate.app/no/compare