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Detekcija mrlja (Blob Detection)×Harisov detektor uglova×
OblastRačunarski vidRačunarski vid
PorodicaMachine learningMachine learning
Godina nastanka19981988
TvoracTony LindebergChris Harris and Mike Stephens
TipMulti-scale feature detectionInterest point detector
Temeljni izvorLindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗Harris, C., & Stephens, M. (1988). A combined corner and edge detector. Alvey Vision Conference, 147–152. link ↗
Drugi naziviConnected component analysis, Region-based detectionHarris Corner Detector, Harris-Stephens Detector, Plessey Operator
Srodne55
SažetakBlob 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.The 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.
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ScholarGateUporedite metode: Blob Detection · Harris Corner Detection. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare