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Segmentácia povodí×Detekcia objektov (blobov)×
OdborPočítačové videniePočítačové videnie
RodinaMachine learningMachine learning
Rok vzniku19791998
TvorcaSerge Beucher and Christian LantuéjoulTony Lindeberg
TypMorphological image segmentationMulti-scale feature detection
Pôvodný zdrojMeyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125. DOI ↗Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗
Ďalšie názvyWatershed transform, Water shedding segmentationConnected component analysis, Region-based detection
Príbuzné55
ZhrnutieWatershed segmentation is a morphological image processing technique that automatically segments an image into distinct regions by treating image intensity as a topographic landscape where each object corresponds to a valley. Introduced by Beucher and Lantuéjoul in 1979 and refined by Meyer, the watershed algorithm is particularly effective for separating touching or overlapping objects.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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ScholarGatePorovnať metódy: Watershed Segmentation · Blob Detection. Získané 2026-06-17 z https://scholargate.app/sk/compare