ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Konturanalyse×Watershed Segmentering×
FagområdeComputer visionComputer vision
FamilieMachine learningMachine learning
Oprindelsesår19851979
OphavspersonSatoshi Suzuki and Keiichi AbeSerge Beucher and Christian Lantuéjoul
TypeShape and contour analysisMorphological image segmentation
Oprindelig kildeSuzuki, 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 ↗
AliasserEdge-based contours, Boundary analysisWatershed transform, Water shedding segmentation
Relaterede55
ResuméContour 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.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Contour Analysis · Watershed Segmentation. Hentet 2026-06-17 fra https://scholargate.app/da/compare