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Kontūru analīze×Ūdensšķirtnes segmentācija×
NozareDatorredzeDatorredze
SaimeMachine learningMachine learning
Izcelsmes gads19851979
AutorsSatoshi Suzuki and Keiichi AbeSerge Beucher and Christian Lantuéjoul
TipsShape and contour analysisMorphological image segmentation
PirmavotsSuzuki, S., & Abe, K. (1985). Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing, 30(1), 32–46. DOI ↗Meyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125. DOI ↗
Citi nosaukumiEdge-based contours, Boundary analysisWatershed transform, Water shedding segmentation
Saistītās55
KopsavilkumsContour analysis is the process of detecting and analyzing the boundaries of objects in images by identifying connected edges and extracting shape information. The Suzuki-Abe algorithm provides an efficient method for finding contours in binary images, enabling shape-based object classification and segmentation.Watershed 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.
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ScholarGateSalīdzināt metodes: Contour Analysis · Watershed Segmentation. Izgūts 2026-06-17 no https://scholargate.app/lv/compare