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Watersheds in digital spaces: an efficient algorithm based on immersion simulations

Luc Vincent; Pierre Soille · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1991

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A fast and flexible algorithm for computing watersheds in digital gray-scale images is introduced. A review of watersheds and related motion is first presented, and the major methods to determine watersheds are discussed. The algorithm is based on an immersion process analogy, in which the flooding of the water in the picture is efficiently simulated using of queue of pixel. It is described in detail provided in a pseudo C language. The accuracy of this algorithm is proven to be superior to that of the existing implementations, and it is shown that its adaptation to any kind of digital grid and its generalization to n-dimensional images (and even to graphs) are straightforward. The algorithm is reported to be faster than any other watershed algorithm. Applications of this algorithm with regard to picture segmentation are presented for magnetic resonance (MR) imagery and for digital elevation models. An example of 3-D watershed is also provided.>

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APA 7

Vincent, L. & Soille, P. (1991). Watersheds in digital spaces: an efficient algorithm based on immersion simulations. https://doi.org/10.1109/34.87344

MLA

Vincent, Luc, and Pierre Soille. "Watersheds in digital spaces: an efficient algorithm based on immersion simulations." 1991. https://doi.org/10.1109/34.87344.

Chicago

Vincent, Luc and Pierre Soille. 1991. "Watersheds in digital spaces: an efficient algorithm based on immersion simulations.". https://doi.org/10.1109/34.87344.

Harvard

Vincent, L. and Soille, P. 1991, Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence, available at: https://doi.org/10.1109/34.87344 [Accessed 7 Aug. 2026].

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Title
Watersheds in digital spaces: an efficient algorithm based on immersion simulations
Author / contributors
Luc Vincent; Pierre Soille
Publisher
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publication year
1991
Language
English

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