An efficient watershed algorithm based on connected components

By Andreas Bieniek, Alina N. Moga. Pattern Recognition, 2000

301 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/71c7de654fe12bc0efabb2b3fd6dbb933ea61a78

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Laurent Najman
2. Leo J. Grady

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Jitendra Malik
3. Xiaogang Wang
4. Alan L. Yuille
5. Trevor Darrell
6. Ming-Hsuan Yang
7. Andrew Zisserman
8. Dacheng Tao

Citations in the corpus

• Power Watershed: A Unifying Graph-Based Optimization Framework (2011, background): “…of the energy minimization problems in our framework, i.e. the cases optimized by graph cuts, shortest path forests and maximum spanning forest algorithms (and watershed in general [12], [26], [13], [71], [34]) have the problem that the optimum solution may not be unique, for example on plateaus.”