The Watershed Transform: Definitions, Algorithms and Parallelization Strategies

By Jos B. T. M. Roerdink, Arnold Meijster. Fundamenta Informaticae, 2000

758 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/1a0963dfd8677bbe68daf156a043ad7d1fa8c6ce

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In Computer Vision and Pattern Recognition

Citations in the corpus

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation (2020, methodology): “Rajinikanth et al. [33] performed the segmentation via the watershed transform techniques [34] with coarse results and limited accuracy.”
Linear Time Maximally Stable Extremal Regions (2008, background): “The watershed segmentation has a long history and has been intensely studied, see [21] for a review.”
Temporal Action Detection with Structured Segment Networks (2017, methodology): “To this end, we repurpose a classic watershed al-gorithm [37], applying it to the 1D signal formed by a sequence of complemented actionness values, as shown in Figure 3.”
TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval (2020, methodology): “The proposals used here are the same as the ones used for MCN and CAL in our previous experiments; (2) TAG [50] that progressively groups top-scored clips with the classical watershed algorithm [33].”
Power Watershed: A Unifying Graph-Based Optimization Framework (2011, methodology): “. A classical approach is to compute a geodesic distance on the plateau [ 71 ] and to use that distance as a way to distinguish between points of the plateau.”
The persistent cosmic web and its filamentary structure I: Theory and implementation (2010, methodology): “The Watershed technique (see Beucher & Lantujoul (1979); Roerdink & Meijster (2000)) was ﬁrst applied to this kind of problem by Platen et al. (2007) as a mean of identifying voids in large scale structures (see also Platen et al. (2008), Colberg et al. (2008) or Aragon-Calvo et al. (2010)), it was…”
Image processing of multiphase images obtained via X‐ray microtomography: A review (2014, methodology): “Methods that fulfill this criterion are Bayesian MRF segmentation [Berthod et al., 1996; Kulkarni et al., 2012], watershed segmentation [Beucher and Lantuejoul, 1979; Vincent and Soille, 1991; Roerdink and Meijster, 2000], and converging active contours [Sheppard et al., 2004].”
Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle (2009, neutral): “The position of the contours produced by watersheds on the plateaus is the subject of many discussions [8], [33], [50].”
A cosmic watershed: the WVF void detection technique (2007, background): “Roerdink & Meijster (2000) give a summary of the most notable schemes.”