Compara mètodes

	Detecció de cantonades Harris	Detecció de blobs
Camp	Visió per computador	Visió per computador
Família	Machine learning	Machine learning
Any d'origen	1988	1998
Autor original	Chris Harris and Mike Stephens	Tony Lindeberg
Tipus	Interest point detector	Multi-scale feature detection
Font seminal	Harris, C., & Stephens, M. (1988). A combined corner and edge detector. Alvey Vision Conference, 147–152.	Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116.
Àlies	Harris Corner Detector, Harris-Stephens Detector, Plessey Operator	Connected component analysis, Region-based detection
Relacionats	5	5
Resum	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.	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.