Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
An overview of morphological filtering
Circuits, Systems, and Signal Processing - Special issue: median and morphological filters
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A minimum spanning tree algorithm with inverse-Ackermann type complexity
Journal of the ACM (JACM)
Introduction to algorithms
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Mathematical Imaging and Vision
Building the Component Tree in Quasi-Linear Time
IEEE Transactions on Image Processing
Milena: Write Generic Morphological Algorithms Once, Run on Many Kinds of Images
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
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We recently introduced the watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, we propose a new thinning paradigm to compute them. More precisely, we introduce a new transformation, called border thinning, that lowers the values of edges that match a simple local configuration until idempotence and prove the equivalence between the cuts obtained by this transformation and the watershed cuts of a map. We discuss the possibility of parallel algorithms based on this transformation and give a sequential implementation that runs in linear time whatever the range of the input map.