K-smallest spanning tree segmentations

5Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Real-world images often admit many different segmentations that have nearly the same quality according to the underlying energy function. The diversity of these solutions may be a powerful uncertainty indicator. We provide the crucial prerequisite in the context of seeded segmentation with minimum spanning trees (i.e. edge-weighted watersheds). Specifically, we show how to efficiently enumerate the k smallest spanning trees that result in different segmentations; and we prove that solutions are indeed found in the correct order. Experiments show that about half of the trees considered by our algorithm represent unique segmentations. This redundancy is orders of magnitude lower than can be achieved by just enumerating the k-smallest MSTs, making the algorithm viable in practice. © 2013 Springer-Verlag.

Cite

CITATION STYLE

APA

Straehle, C., Peter, S., Köthe, U., & Hamprecht, F. A. (2013). K-smallest spanning tree segmentations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8142 LNCS, pp. 375–384). https://doi.org/10.1007/978-3-642-40602-7_40

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free