Discrete Dynamics in Nature and Society · 2008 · 214 citations · 8 references
ComputingComputer ScienceBiomedical ImagingComputer VisionImage InterpretationEdge DetectionImage AnalysisImage SegmentationMedical Image AnalysisMorphological SegmentationShape AnalysisContour DetectionGrayscale MorphologyMedical Image SegmentationMorphological Image SegmentationRegion-based SegmentationSegmentationSimple AlgorithmWatershed Segmentation
Watershed segmentation is a fast, powerful technique for contour and region‑based segmentation that relies on ridge structures to delineate object boundaries. The study proposes a new segmentation method for color, gray‑scale MR medical images and aerial images. The method employs gray‑scale morphology and a marker‑controlled watershed algorithm implemented in MATLAB, converting edge maps into ridges for region‑based segmentation.
Segmentation, a new method, for color, gray‐scale MR medical images, and aerial images, is proposed. The method is based on gray‐scale morphology. Edge detection algorithm includes function edge and marker‐controlled watershed segmentation. It features the simple algorithm implemented in MATLAB. The watershed segmentation has been proved to be a powerful and fast technique for both contour detection and region‐based segmentation. In principle, watershed segmentation depends on ridges to perform a proper segmentation, a property that is often fulfilled in contour detection where the boundaries of the objects are expressed as ridges. For region‐based segmentation, it is possible to convert the edges of the objects into ridges by calculating an edge map of the image. Watershed is normally implemented by region growing, based on a set of markers to avoid oversegmentation.
8
Image analysis and mathematical morphology
Computer Graphics and Image Processing · 1982 · 8.2K citations
Image Analysis and Mathematical Morphology.
P. J. Diggle, J. Serra · Biometrics · 1983 · 3.9K citations