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Анализ на контури×Сегментиране чрез вододел×
ОбластКомпютърно зрениеКомпютърно зрение
СемействоMachine learningMachine learning
Година на възникване19851979
СъздателSatoshi Suzuki and Keiichi AbeSerge Beucher and Christian Lantuéjoul
ТипShape and contour analysisMorphological image segmentation
Основополагащ източникSuzuki, 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 ↗
Други названияEdge-based contours, Boundary analysisWatershed transform, Water shedding segmentation
Свързани55
РезюмеContour 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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Contour Analysis · Watershed Segmentation. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare