Higher-dimensional segmentation by minimum-cut algorithm

Hiroshi Ishikawa, Davi Geiger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is important in many applications of 3D and higher dimensional segmentation that the resulting segments of voxels are not required to have only one connected component, as in some of extant methods. Indeed, it is generally necessary to be able to automatically determine the appropriate number of connected components. More generally, for a larger class of applications, the segments should have no topological restrictions at all. For instance, each connected component should be allowed to have as many holes as appropriate to fit the data. We propose a method based on a graph algorithm to automatically segment 3D and higher-dimensional images into two segments without user intervention, with no topological restriction on the solution, and in such a way that the solution is optimal under a precisely defined optimization criterion.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005
Pages488-491
Number of pages4
StatePublished - Dec 1 2005
Event9th IAPR Conference on Machine Vision Applications, MVA 2005 - Tsukuba Science City, Japan
Duration: May 16 2005May 18 2005

Publication series

NameProceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005

Other

Other9th IAPR Conference on Machine Vision Applications, MVA 2005
CountryJapan
CityTsukuba Science City
Period5/16/055/18/05

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Ishikawa, H., & Geiger, D. (2005). Higher-dimensional segmentation by minimum-cut algorithm. In Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 (pp. 488-491). (Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005).