ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Сегментация методом водораздела×Морфологические операции над изображениями×
ОбластьКомпьютерное зрениеКомпьютерное зрение
СемействоMachine learningMachine learning
Год появления19791982
Автор методаSerge Beucher and Christian LantuéjoulJean Serra
ТипMorphological image segmentationSet theory and topological image processing
Основополагающий источникMeyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125. DOI ↗Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press. link ↗
Другие названияWatershed transform, Water shedding segmentationMathematical morphology, Morphological filtering
Связанные55
СводкаWatershed 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.Morphological image processing, introduced by Jean Serra in 1982, is a technique based on set theory that reshapes and analyzes image regions using geometric structuring elements. Core operations include erosion and dilation, which can be combined into more complex operations like opening and closing, enabling noise removal, edge detection, and object analysis.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Watershed Segmentation · Image Morphology Operations. Получено 2026-06-17 из https://scholargate.app/ru/compare