### 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 language | English |
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Title of host publication | Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 |

Pages | 488-491 |

Number of pages | 4 |

Publication status | Published - 2005 Dec 1 |

Event | 9th IAPR Conference on Machine Vision Applications, MVA 2005 - Tsukuba Science City, Japan Duration: 2005 May 16 → 2005 May 18 |

### Publication series

Name | Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 |
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### Conference

Conference | 9th IAPR Conference on Machine Vision Applications, MVA 2005 |
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Country | Japan |

City | Tsukuba Science City |

Period | 05/5/16 → 05/5/18 |

### ASJC Scopus subject areas

- Computer Vision and Pattern Recognition

## Cite this

*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).